The Push programming language and the PushGP genetic programming system implemented in Clojure.
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README.txt Lee Spector (firstname.lastname@example.org), started 20100227 See version history at https://github.com/lspector/Clojush/commits/master This is the README file accompanying Clojush, an implementation of the Push programming language and the PushGP genetic programming system in the Clojure programming language. Among other features this implementation takes advantage of Clojure's facilities for multi-core concurrency. Use Java's -XX:+UseParallelGC option to take maximum advantage of this feature. AVAILABILITY https://github.com/lspector/Clojush/ REQUIREMENTS To use this code you must have a Clojure programming environment; see http://clojure.org/. The current version of clojush requires clojure 1.3. Clojure is available for most OS platforms. A good starting point for obtaining and using Clojure is http://dev.clojure.org/display/doc/Getting+Started. QUICKSTART Using Leiningen (from https://github.com/technomancy/leiningen) you can run an example from the OS command line (in the Clojush directory) with a call like: lein run clojush.examples.simple-regression This will load everything and run PushGP on a simple symbolic regression problem (symbolic regression of y=x^3-2x^2-x). Although the details will vary from run to run, and it's possible that it will fail, this usually succeeds in a few generations. Another simple (perhaps simpler) option is to use Clooj. To run an example in Clooj, download and launch the latest "standalone" build from https://github.com/arthuredelstein/clooj, open the Clojush project, open an example file within Clojush/src/clojush/examples, and select REPL > Evaluate entire file. In other IDEs there will be other ways to run the examples. For example, in Eclipse/Counterclockwise you can simply open an example and select Clojure > Load clojure file in REPL. Similarly, in Clooj For large-scale runs you may want to provide additional arguments to java in order to allow access to more memory and/or to take maximal advantage of Clojure's concurrency support in the context of clojush's reliance on garbage collection. For example, you might want to provide a rguments such as -Xmx2000m and -XX:+UseParallelGC. Details will depend on the method that you use to launch your code. DESCRIPTION Clojush is a version of the Push programming language for evolutionary computation, and the PushGP genetic programming system, implemented in clojure. More information about Push and PushGP can be found at http://hampshire.edu/lspector/push.html. Clojush derives mainly from Push3 (for more information see http://hampshire.edu/lspector/push3-description.html, http://hampshire.edu/lspector/pubs/push3-gecco2005.pdf) but it is not intended to be fully compliant with the Push3 standard and there are a few intentional differences. It was derived most directly from the Scheme implementation of Push/PushGP (called Schush). There are several differences between Clojush and other versions of Push3 -- for example, almost all of the instruction names are different because the "." character has special significance in Clojure -- and these are listed below. If you want to understand the motivations for the development of Push, and the variety of things that it can be used for, you should read a selection of the documents listed at http://hampshire.edu/lspector/push.html, probably starting with the 2002 Genetic Programming and Evolvable Machines article that can be found at http://hampshire.edu/lspector/pubs/push-gpem-final.pdf. But bear in mind that Push has changed over the years, and that Clojush is closest to Push3 (references above). Push can be used as the foundation of many evolutionary algorithms, not only PushGP (which is more or less a standard GP system except that it evolves Push programs rather than Lisp-style function trees -- which can make a big difference!). It was developed primarily for "meta-genetic-programming" or "autoconstructive evolution" experiments, in which programs and genetic operators co-evolve or in which programs produce their own offspring while also solving problems. But it turns out that Push has a variety of uniquely nice features even within a more traditional genetic programming context; for example it makes it unusually easy to evolve programs that use multiple data types, it provides novel and automatic forms of program modularization and control structure co-evolution, and it allows for a particularly simple form of automatic program simplification. Clojush can serve as the foundation for other evolutionary algorithms, but only the core Push interpreter and a version of PushGP are provided here. USAGE Example calls to PushGP are provided in other accompanying files. Push programs are run calling run-push, which takes as arguments a Push program and a Push interpreter state that can be made with make-push-state. If you are planning to use PushGP then you will want to use this in the error function (a.k.a. fitness function) that you pass to the pushgp function. Here is a simple example of a call to run-push, adding 1 and 2 and returning the top of the integer stack in the resulting interpreter state: (top-item :integer (run-push '(1 2 integer_add) (make-push-state))) If you want to see every step of execution you can pass an optional third argument of true to run-push. This will cause a representation of the interpreter state to be printed at the start of execution and after each step. Here is the same example as above but with each step printed: (top-item :integer (run-push '(1 2 integer_add) (make-push-state) true)) See the "parameters" section of the code for some parameters that will affect execution, e.g. whether code is pushed onto and/or popped off of the code stack prior to/after execution, along with the evaluation limits (which can be necessary for halting otherwise-infinite loops, etc.). Run-push returns the Push state that results from the program execution; this is a Clojure map mapping type names to data stacks. In addition, the map returned from run-push will map :termination to :normal if termination was normal, or :abnormal otherwise (which generally means that execution was aborted because the evaluation limit was reached. Random code can be generated with random-code, which takes a size limit and a list of "atom generators." Size is calculated in "points" -- each atom and each pair of parentheses counts as a single point. Each atom-generator should be a constant, or the name of a Push instruction (in which case it will be used literally), or a Clojure function that will be called with no arguments to produce a constant or a Push instruction. This is how "ephemeral random constants" can be incorporated into evolutionary systems that use Clojush -- that is, it is how you can cause random constants to appear in randomly-generated programs without including all possible constants in the list of elements out of which programs can be constructed. Here is an example in which a random program is generated, printed, and run. It prints a message indicating whether or not the program terminated normally (which it may not, since it may be a large and/or looping program, and since the default evaluation limit is pretty low) and it returns the internal representation of the resulting interpreter state: (let [s (make-push-state) c (random-code 100 ;; size limit of 100 points (concat @registered-instructions ;; all registered instrs (list (fn  (rand-int 100)) ;; random integers from 0-99 (fn  (rand)))))] ;; random floats from 0.0-1.0 (printf "\n\nCode: %s\n\n" (apply list c)) (run-push c s)) If you look at the resulting interpreter state you will see an "auxiliary" stack that is not mentioned in any of the Push publications. This exists to allow for auxiliary information to be passed to programs without using global variables; in particular, it is used for the "input instructions" in some PushGP examples. One often passes data to a Push program by pushing it onto the appropriate stacks before running the program, but in many cases it can also be helpful to have an instruction that re-pushes the input whenever it is needed. The auxiliary stack is just a convenient place to store the values so that they can be grabbed by input instructions and pushed onto the appropriate stacks when needed. Perhaps you will find other uses for it as well, but no instructions are provided for the auxiliary stack in Clojush (aside from the problem-specific input functions in the examples). The pushgp function is used to run PushGP. It takes all of its parameters as keyword arguments, and provides default values for any parameters that are not provided. See the pushgp defn in pushgp/pushgp.clj for details. The single argument that must be provided (actually it too has a default, but it makes no sense to rely on that) is :error-function, which should be a function that takes a Push program and returns a list of errors. Note that this assumes that you will be doing single-objective evolution with the objective being thought of as an error to be minimized. This assumption not intrinsic to Push or PushGP; it's just the simplest and most standard thing to do, so it's what I've done here. One could easily hack around that. In the most generic applications you'll want to have your error function run through a list of inputs, set up the interpreter and call run-push for each, calculate an error for each (potentially with penalties for abnormal termination, etc.), and return a list of the errors. Not all of the default arguments to pushgp will be reasonable for all problems. In particular, the default list of atom-generators -- which is ALL registered instructions, a random integer generator (in the range from 0-99) and a random float generator (in the range from 0.0 to 1.0) -- will be overkill for many problems and is so large that it may make otherwise simple problems quite difficult because the chances of getting the few needed instructions together into the same program will be quite low. But on the other hand one sometimes discovers that interesting solutions can be formed using unexpected instructions (see the Push publications for some examples of this). So the set of atom generators is something you'll probably want to play with. The registered-for-type function can make it simpler to include or exclude groups of instructions. This is demonstrated in some of the examples. Other pushgp arguments to note include those that control genetic operators (mutation, crossover, and simplification). The specified operator probabilities should sum to 1.0 or less -- any difference between the sum and 1.0 will be the probability for "straight" (unmodified) reproduction. The use of simplification is also novel here. Push programs can be automatically simplified -- to some extent -- in a very straightforward way: because there are almost no syntax constraints you can remove anything (one or more atoms or sub-lists, or a pair of parentheses) and still have a valid program. So the automatic simplification procedure just iteratively removes something, checks to see what that does to the error, and keeps the simpler program if the error is the same (or lower!). Automatic simplification is used in this implementation of PushGP in three places: 1. There is a genetic operator that adds the simplified program to the next generation's population. The use of the simplification genetic operator will tend to keep programs smaller, but whether this has benificial or detrimental effects on search performance is a subject for future research. 2. A specified number of simplification iterations is performed on the best program in each generation. This is produced only for the sake of the report, and the result is not added to the population. It is possible that the simplified program that is displayed will actually be better than the best program in the population. Note also that the other data in the report concerning the "best" program refers to the unsimplified program. 3. Simplification is also performed on solutions at the ends of runs. Note that the automatic simplification procedure will not always find all possible simplifications even if you run it for a large number of iterations, but in practice it does often seem to eliminate a lot of useless code (and to make it easier to perform further simplification by hand). If you've read this far then the best way to go further is probably to read and run the examples. IMPLEMENTATION NOTES A Push interpreter state is represented here as a Clojure map that maps type names (keywords) to stacks (lists, with the top items listed first). Push instructions are names of Clojure functions that take a Push interpreter state as an argument and return it modified appropriately. The define-registered macro is used to establish the definitions and also to record the instructions in the global list registered-instructions. Most instructions that work the same way for more than one type are implemented using a higher-order function that takes a type and returns a function that takes an interpreter state and modifies it appropriately. For example there's a function called popper that takes a type and returns a function -- that function takes a state and pops the right stack in the state. This allows us to define integer_pop with a simple form: (define-registered integer_pop (popper :integer)) In many versions of Push RUNPUSH takes initialization code or initial stack contents, along with a variety of other parameters. The implementation of run-schush here takes only the code to be run and the state to modify. Other parameters are set globally in the parameters section below. At some point some of these may be turned into arguments to run-push so that they aren't global. Miscellaneous differences between clojush and Push3 as described in the Push3 specification: - Clojush instruction names use "_" instead of "." since the latter has special meaning when used in Clojure symbols. - Equality instructions use "eq" rather than "=" since the latter in not explicitly allowed in clojure symbols. - for similar reasons +, -, *, /, %, <, and > are replaced with add, sub, mult, div, mod, lt, and gt. - Boolean literals are true and false (instead of TRUE and FALSE in the Push3 spec). The original design decision was based on the fact that Common Lisp's native Boolean literals couldn't used without conflating false and the empty list (both NIL in Common Lisp). - Clojush adds exec_noop (same as code_noop). - Clojush includes an execution time limit (via the parameter evalpush-time-limit) that may save you from exponential code growth or other hazards. But don't forget to increase it if you expect legitimate programs to take a long time. Push3 stuff not (yet) implemented: - NAME type/stack/instructions - Other missing instructions: *.DEFINE, CODE.DEFINITION, CODE.INSTRUCTIONS - The configuration code and configuration files described in the Push3 spec have not been implemented here. The approach here is quite different, so this may never be implemented TO DO (SOMETIME, MAYBE) - Clean up issues involving Push globals and PushGP parameters for the same or similar things. - Implement remaining instructions in the Push3 specification. - Add more examples. - Add support for seeding the random number generator. - Add improved genetic operators, e.g. fair mutation/crossover and constant-perturbing mutations. - Improve the automatic simplification algorithm. - Possibly rename the auxiliary stack the "input" stack if no other uses are developed for it. - Write a "sufficient-args" fn/macro to clean up Push instruction definitions. VERSION HISTORY -- NOW OBSOLETE. See https://github.com/lspector/Clojush/commits/master 20100227: - First distributed version. 20100301: - Added (shutdown-agents) for proper termination. 20100306: - Added history (of total errors of ancestors) to individuals. - Commented out (shutdown-agents) because it prevents multiple runs in a single launch of a Clojure REPL. 20100307: - Fixed bug in history: reproductive auto-simplification added was adding duplicate items. 20100314: - Added instructions: *_shove, code_extract, code_insert, code_subst, code_contains, code_container, code_position, code_discrepancy, *_rand. NOTE that the presence of *_rand instructions means that programs produced using the full set of instructions may be non-deterministic. As of this writing pushgp (via evaluate-individual) will evaluate an individual only once, so it will always have whatever fitness value it had upon first testing. - Added globals to support integer_rand and float_rand: min-random-integer, max-random-integer, min-random-float max-random-float. - Fixed bug in code_car that could produce nil. - Made execute-instruction safe for nil (although it shouldn't arise anyway). - Added stress-test for testing and debugging new Push instructions. See the stress-test documentation string for details. - Implemented size limits on intermediate results on code stack (in code_cons, code_list, code-append, code_insert, code_subst, exec_s, exec_y). - Fixed bug in exec_s (was always a noop previously). 20100319: - Added problem-specific-report function (to be customized per problem). This can also be a convenient place to put other stuff that you want done once per generation. - Added support for saving lists of ancestors (maternal line only) along with global parameters to turn both this and the saving of total-error histories on and off. - Added missing calls to "keep-number-reasonable" in numeric Push instructions. This eliminates some potential crashes from runaway number growth. 20100320: - Added print-ancestors-of-solution parameter and code. - Print simplification in report only with non-zero value for report-simplifications parameter. - Added sextic polynomial regression example. This example also demonstrates the use of fitness penalties for abnormally terminating programs. - Added a new argument to problem-specific-report (NOTE: not backward compatible). 20100417: - Added thread-local random number generator objects to avoid contention. - Print parameters at the start of pushgp. - Added readme comments about concurrency, -Xmx2000m, and -XX:+UseParallelGC. - Converted time limit code to use System/nanoTime (thanks to Brian Martin). This means that time limits must now be expressed in nanoseconds rather than milliseconds, and I believe it will eliminate contention for shared Date objects (but this should be checked; if there is contention then we should revert to using Date and use thread-local date objects as is being done with the random number generator objects). - Added print-return utility function for debugging. - Added a new Push instruction, code_wrap, which pushes a 1-item list containing the previous top item of the code stack. - Added a new Push instruction, code_map, which acts much like Lisp's (or Scheme's or Clojure's) "map" functions, using the top item on the exec stack as the function to map and the top item on the code stack as the list to map it down. The list of results is left on top of the code stack. This is implemented as a "macro" instruction that expands into a Push code fragment that: 1) for each item in the list on top of the code stack (or for the single non-list item that is there) quotes the item onto the code stack and then runs the code that's on top of the exec stack; 2) uses code_wrap to push a list containing the last result onto the code stack; 3) executes as many instances of code_cons as are necessary to add all of the other results onto the list. Note that this will act like an ordinary "map" function only when the code on the exec stack leaves a single output on the code stack in place of each input on the code stack; if it consumes or produces more or less code then the effect will be quite different. 20100502: - Made thread-local random integer function (lrand-int) safe for bignums, but arguments greater than 2^31-1 are treated as if they were 2^31-1 (2147483647). 20100526: - Reimplemented subst to use clojure.walk/postwalk-replace. Also fixed comment, which described args backwards. (The behavior was correct, emulating Common Lisp subst.) 20100918: - Created Eclipse project. - Deleted re-load/backtrace utils. - Removed shuffle, as it is now in clojure.core (in Clojure 1.2). - Removed gratuitous def in define-registered. - Added atom for instruction-table. - Added atom for registered-instructions; NOTE: requires user code that refers to registered-instructions to refer to @registered-instructions instead. (Example odd.clj changed to reflect this.) - Added to-do item "Convert structs to records, which should be faster. Experiments with Clojure 1.2 show this to be faster but there are not good examples yet to serve as the basis for changes. - Added atoms for global-atom-generators and global-max-points-in-program. - Changed pushgp to take keyword arguments rather than a parameter map. NOTE: this requires calls to pushgp to be written differently. Updated examples to reflect this. 20100921: - Removed random-element in favor of rand-nth. - Cleaned up indentation, miscellaneous other cosmetic things. - Added namespaces for all example files. - Updated README to mention requirement for clojure 1.2 and to remove mention of ClojureX which has been discontinued. - Converted structures to records (a clojure 1.2 feature, should be faster). 20101005: - Added error-handlers to agents. 20101014: - [Artificial ant, krypto, tg8, decimation] - Added articial ant example from Koza (via Luke). - Added "tg8" integer symbolic regression problem. - Added krypto number puzzle example. - Added pushgp "decimation" feature, in which elimination tournaments, conducted after fitness testing, reduce the size of the population to a specified fraction of its original size (specified in a decimation-ratio argument to pushgp; the tournament sized is specified via decimation-tournament-size). The ordinary tournament-size parameter is still used for subsequent selection from the decimated population. Any specified trivial geography applies both to decimation and to subsequent selection. 20101017: - Reverted from records to structs; wasn't significantly faster and structs allow for greater flexibility in use of state as map. 20101102: - Switched to new clojure.core/frequencies from depricated seq-utils/frequencies (h/t Kyle Harrington), and similarly for flatten. - Added :include-randoms keyword argument for registered-for-type. Defaults to true, but if specified as false then instructions ending with "_rand" will be excluded. - Raised invalid output penalty in tg8 (it was lower than reasonable errors for that problem). 20101103: - Converted evalpush-limit and evalpush-time-limit into vars (global-evalupush-limit and global-evalpush-time-limit) bound to atoms that are reset by calls to pushgp (keyword arguments :evalpush-limit and :evalpush-time-limit). - Changed pushgp parameters in the tg8.clj example. 20101104: - Implemented stackless tagging (see http://push.i3ci.hampshire.edu/ 2010/10/28/stackless-tagging/). Tag instructions take one of the following forms: tag_<type>_<number> create tage/value association, with the value taken from the stack of the given type and the number serving as the tag untag_<number> remove the association for the closest-matching tag tagged_<number> push the value associated with the closest-matching tag onto the exec stack (or no-op if no associations). Here "closest-matching" means the tag with lowest number that is greater than or equal to the number of the tag being matched, or the lowest-numbered tag if none meet this criterion. Tag instructions are not implemented in the same way as other instructions; they are detected and handled specially by the interpreter (see execute-instruction). Tag instructions can be included in pushgp runs by using the new ephemeral random constant functions tag-instruction-erc, untag-instruction-erc, and tagged-instruction-erc, each of which takes a limit (for the numerical part) as an argument. - Added examples using tags: tagged_ant, tagged_regression, and tagged_tg8. 20101106: - Tweaked parameters in ant examples; among other things, increased simplification since bloat was an issue. Also added some evolved solutions in comments. 20101107: - Added Koza's lawnmower problem example; this demonstrates how to add a new type/stack on a problem-specific basis, without altering clojush.clj. 20101204: - Added pushgp-map, which allows pushgp calls on maps of arguments, and a demonstration of its use in argmap_regression.clj. - Added :gen-class and -main definition (thanks Kyle Harrington). - Fixed eval-push termination to return :abnormal for exceeding time-limit (thanks Kyle Harrington). 20101205: - Added modified version of Kyle's version of the intertwined spirals problem. - Minor changes to this README. 20101208: - Added alternative methods for node selection, used in mutation and crossover (drafted by Brian Martin, with suggestions from Kyle Harrington). This introduced three new globals: global-node-selection-method, global-node-selection-leaf-probability, and global-node-selection-tournament-size, each of which holds an atom, and three new parameters to pushgp: node-selection-method, node-selection-leaf-probability, and node-selection-tournament-size. The node-selection-method can be :unbiased (in which case nodes are selected using the uniform distribution that was previously used -- this is the default), :leaf-probability (in which case the value of the node-selection-leaf-probability argument, which defaults to 0.1, specifies the probability that leaves, as opposed to internal nodes, will be selected -- this is the method used by Koza and others in tree-based GP), or :size-tournament (in which case the value of the node-selection-tournament-size argument, which defaults to 2, determines the tournament size for node tournaments, with the largest subtree in the tournament set being selected). 20110111: - Added zipper stack and functions (thanks to Kyle Harrington for draft code, although this was re-written). - Added registered-nonrandom function. - Modified odd.clj example to use registered-nonrandom. - Added examples/dsoar.clj, a version of the "Dirt-Sensing, Obstacle-Avoiding Robot" (DSOAR) problem first described in: Spector, L. 1996. Simultaneous Evolution of Programs and their Control Structures. In Advances in Genetic Programming 2, edited by P. Angeline and K. Kinnear, pp. 137-154. Cambridge, MA: MIT Press. http://helios.hampshire.edu/lspector/pubs/AiGP2-post-final-e.pdf This version was written by Brian Martin in 2010-2011. 20110118: - Added support for tagged_code_<number> instructions. These are like tagged_<number> instructions except that retrieved values are pushed onto the code stack rather than the exec stack. Without these the only way to get tagged values onto the code stack is to wrap values with code_quote prior to tagging. An alternative approach is to add new tagging instructions that automatically perform code_quote wrapping, but for full generality that would require new instructions for each type; also quote-tagged values would always be destined for the code stack, while the scheme adopted here allows any stored value to be retrieved either to exec or to code. - A value of 0 for the evalpush-time-limit parameter of pushgp now means that no time limit will be enforced. This is also now the default. 20110322: - Tag reference bug fixed in closest-association (>= changed to <=). - Added mux (multiplexer) example (a couple of approaches in one file). 20110409: - Added support for no-pop tagging through a var called global-pop-when-tagging (holding an atom with a boolean value) and a boolean argument to pushgp called pop-when-tagging. The defaults are true, for backwards compatibility. If @global-pop-when-tagging is false (which will result from passing false as a :pop-when-tagging keyword argument to pushgp) then executing instructions of the form tag_<type>_<number> will tag a value as usual, but the tagged item will not be popped from its source stack. - Removed no-pop hackage from mux example (thanks Kyle). 20110424: - Added Gaussian mutation for floating point literals. This is a genetic operator on par with ordinary mutation, crossover, and simplification, with the probability for applying this operator set with the gaussian-mutation-probability argument to pushgp (which defaults to zero). The behavior of this operator, when used, is controlled by two other arguments to pushgp, gaussian-mutation-per-number-mutation-probability (which is the probability that any particular floating point number in the program will actually be mutated -- this defaults to 0.5) and gaussian-mutation-standard-deviation (which specifies the standard deviation of the Gaussian noise generator that is used to produce changes to numbers -- this defaults to 0.1). - Added examples/gaussian_mutation_demo.clj to demonstrate Gaussian mutation. - Added examples/korns_regression_p12.clj, a symbolic regression problem based on Michael Korns's draft chapter from GPTP11. 20110505: - Added complex number support. New instructions for the 'complex' stack include: pop, dup, swap, rot, flush, eq, stackdepth, yank, yankdup, shove, rand, add, sub, mult, divide, fromfloat, frominteger, fromfloats, fromintegers, conjugate, magnitude, and principal_sqrt. (Brian Martin) 20110517: - Added a "scaled-errors" function to support error-scaling as described by Maarten Keijzer in Scaled Symbolic Regression, in Genetic Programming and Evolvable Machines 5(3), pp. 259-269, September 2004. This must be used in a problem's error function, and then the outputs of the evolved program must be "unscaled." See the documentation string for scaled-errors and also examples/scaled_sextic.clj for details. - Added examples/scaled_sextic.clj to demonstrate the use of scaled-errors. - Changed examples/sextic.clj to use squared errors and an error threshold, in order to facilitate comparisons between the versions that do and don't use error scaling. - Made minor changes to the korns_regression_p12 example. 20110526: - Enforce size limits on zipper manipulation results. 20110607: - Added overlap utility function, overlap-demo (which just prints some examples to show how overlap works), and code_overlap instruction. Overlap can be applied to any two (possibly nested) things and it returns a number between 0 (meaning no overlap) and 1 (meaning exact match). The overlap utility function returns a ratio, but the code_overlap instruction pushes a float. - Removed complex number support from 20110505. There were previous reports of problems and I've noticed problems from the fact that (apply + ()) => zero (as opposed to 0) in the clojush namespace defined by the code as revised for complex number support. If someone knows how to re-introduce complex number support without such problems then please let me know. 20110618: - Switched to Kyle Harrington's version of overlap; it's more clear, possibly faster, and may fix a hard-to-trace bug that cropped up in a long evolutionary run (?). 20110624: - Replaced lawnmower and dsoar examples with bugfixed versions (thanks to Kyle Harrington). - Added namespace and made miscellaneous other changes to clojush-tests.clj. - Added support for tagged-code macros. Tagged-code macro calls have the effect of code instructions, but they take their code arguments from the tag space and they tag their code return values. They are implemented as macros to leverage the existing code instruction set; note that this means that a single call will contribute more than one iteration step toward the evalpush-limit. Tagged-code macros appear in programs as hash maps that map :tagged_code_macro to true, :instruction to a code instruction, :argument_tags to a sequence of tags to be used to acquire arguments, and :result_tags to a sequence of tags to be used for tagging results. Execution of a macro expands the needed code onto the exec stack to grab arguments from the tag space and push them on the code stack, execute the code instruction, and tag results. Note that results will also be left on the code stack if global-pop-when-tagging is false. Conceptually, tag values are "baked in" to these macros in much the same way that tag values are "baked in" to the instruction names for stackless tag instructions; we use hash maps simply because there is more information to bake in and this prevents us from having to parse the names (which would get messy and also waste time). Because the maps make it difficult to read programs, however, a utility function called abbreviate-tagged-code-macros is provided to produce copies of programs with more human-readable (but not currently executable) representations of tagged-macro calls. A tagged-code-macro-erc is provided to generate random tagged-code macros in pushgp runs. A new example, codesize20, provides a simple demonstration of the use of tagged-code macros. - Replaced walk-based code-manipulation with walklist functions that only traverse list structure. This fixes an interaction between map literals (e.g. tagged-code macros) and program structure. 20110629: - Fixed abbreviate-tagged-code-macros printing of empty lists. - Added seq condition to walklist to permit walking of seqs that aren't actually full-fledged lists. 20110702: - Several fixes/refinements to tagged-code macros: - Fixed incorrect no-op of arg-free calls with empty tag space. - Added :additional_args to tagged-code macro structure; the value should be a list of items and these will be executed in order before calling the macro's instruction. - Added optional 5th arg to tagged-code-macro-erc; this should be a function of zero args that will be called to produce the value of :additional_args (e.g. if you want to have one random integer arg then you could specify a 5th arg of (fn  (list (lrand-int 101))). - Changed format produced by abbreviate-tagged-code-macros to handle :additional_args and to be slightly more concise. 20110714: - Added "trace" argument to eval-push and run-push. If this is true then the resulting state will map :trace to a list of executed instructions and literals, in reverse order of execution. If the argument is :changes then instructions that have no effect on the state will be excluded. 20110809: - Several additions/enhancements by Kyle Harrington: - Converted problem-specific-report to a parameter in pushgp. - Added reporting of program repeat counts in population. - Added "error-reuse" parameter to pushgp for use in stochastic and dynamic problems (for which reuse would be turned off). - Added examples/mackey_glass_int.clj, a symbolic regression problem as described in Langdon & Banzhaf's 2005 paper (citation in file). - Added examples/pagie_hogeweg.clj problem, a difficult symbolic regression problem when coevolution is not used. Introduced by Pagie & Hogeweg's 1997 paper (citation in file). 20110911: - Switched from Eclipse to Clooj/Leiningen for development and rearranged the project for this. - Added calls to end of all example files. - Examples can be run from the OS command line (assuming that leiningen is available) with calls like: lein run examples.simple-regression - Added local-file dependency and used file* for file access. - Removed ant and tagged-ant examples because of bugs related to confusion of push interpreted states and ant world states. 20111104: - Added string stack and a variety of string stack instructions. - Added two example pushgp runs that use the string stack in the file examples/string.clj. 20111112: - Obsoleted this version history in favor of the commit logs at https://github.com/lspector/Clojush/commits/master ACKNOWLEDGEMENTS This material is based upon work supported by the National Science Foundation under Grant No. 1017817. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.