Further reading

Further reading

Where the mechanisms in this library come from. Nothing here is required to use it, but every design decision in tinyhivemind-hive traces to something on this page, and the Glossary links each term to the page that uses it.

The swarm mechanisms

Stigmergy. Coordination through traces left in a shared medium rather than through messages between agents. Named by Pierre-Paul Grassé in 1959 from termite mound construction.

• Stigmergy
• Swarm intelligence
• Self-organization

Used by: Trace grammar.

Pheromone trails and evaporation. A trail reinforced by use and weakened by time. Evaporation is the part that matters here: without it the first path found stays the only path found.

• Pheromone
• Ant colony optimization
• Exponential decay and half-life

Used by: the salience field in Hive episodes.

Quorum sensing. A decision taken when a threshold number of participants is detected locally, rather than by counting a majority globally. The term comes from bacteria; the version this library implements is the one honeybee swarms use to settle on a nest site.

• Quorum sensing
• Swarming (honey bee)
• Thomas Seeley, whose Honeybee Democracy is the book-length account of nest-site selection

Used by: the quorum fold in Hive episodes, and both of its bounds in Episode policy.

Cross-inhibition. Scouts advertising one site deliver stop signals to scouts advertising another, suppressing the advocate rather than devaluing the site. It is what lets a swarm break a tie between two good options, and the same asymmetry is why an !object in this library names a message rather than a topic.

• Swarming (honey bee)
• Lateral inhibition, the same shape in neural systems

Used by: Hive episodes.

Response thresholds. Each individual has a private threshold for a task, acts when local stimulus exceeds it, and stays idle otherwise. Division of labour falls out of the threshold distribution without anybody assigning anything.

• Task allocation and partitioning of social insects
• Eusociality

Used by: the attention market in Hive episodes.

Pandemonium. Oliver Selfridge's 1959 architecture, in which "demons" shout with a volume proportional to how well they match, and a decision demon takes the loudest. It is the response-threshold model arrived at from the artificial intelligence side rather than the entomology side, and taking the loudest one is exactly the argmax that enforces one message, one turn.

• Pandemonium architecture
• Arg max

Used by: Hive episodes.

How groups of people decide, and fail to

The failure modes this library designs against are not hypothetical, and none of them are specific to language models.

• Wisdom of the crowd and Condorcet's jury theorem, which is the formal reason an independent vote is such a strong control. The theorem assumes independence, and a shared transcript destroys it.
• Information cascade. The reason the opening round is blind. Without it, accuracy in the benchmark falls 24 points to the level of a single agent. See Benchmarks.
• Groupthink and the Asch conformity experiments. Convergence is a warning signal as much as a success signal, which is why the turn budget is deliberately small.
• Collective intelligence. Woolley et al., Evidence for a Collective Intelligence Factor in the Performance of Human Groups, Science 2010, found equality of conversational turn-taking to be one of the few robust predictors of group performance. That result is why the attention market carries a dominance penalty at all.
• Plurality voting, which is how the vote control arm decides.

Multi-agent language models

• Self-Consistency Improves Chain of Thought Reasoning in Language Models. Sample several answers independently and take the plurality. This is the matched-budget control in Benchmarks, and any multi-agent result reported without it is close to meaningless.
• Improving Factuality and Reasoning in Language Models through Multiagent Debate. The debate setup this library's episode is a bounded, auditable version of.
• Generative Agents: Interactive Simulacra of Human Behavior. The memory stream retrieval score, a weighted sum of recency, importance and relevance, is the shape the salience field borrows. Where its paper and its released code disagree on weights, this library follows the code.
• Why Do Multi-Agent LLM Systems Fail?. A taxonomy of observed failures. Step repetition and premature termination both appear in it, and both are protocol bugs rather than model bugs, which is why repetition_cap and the phase gate exist.

On communication topology: sparse topologies have been reported to match or beat fully connected ones in multi-agent debate at substantially lower cost. That finding, together with the conformity results above, is the empirical half of the argument in ADR 0002; the other half is that a type carrying two authorized speakers would make the charter's one-message-one-turn rule unenforceable.

The machinery

Vocabulary this wiki uses without explaining it.

• Fold and pure function. Every decision in tinyhivemind-core and tinyhivemind-hive is one of these.
• Idempotence. Why an agent that catches up late folds to the same standing as one that watched live.
• Fixed-point arithmetic. Why every payload derives Eq and every episode replays exactly.
• Deadlock. What a below-majority quorum threshold produces, and why the threshold has a lower bound.
• Watermark. How continuous sharing tracks what an agent has already seen.
• Idempotency key. What the MentionTurnQueue port is keyed by.

In this repository

where	what
crates/tinyhivemind-hive/src/trace/	the stigmergic grammar
crates/tinyhivemind-hive/src/salience/	recency decay, importance, relevance
crates/tinyhivemind-hive/src/quorum/	standings, cross-inhibition, consensus
crates/tinyhivemind-hive/src/attention/	the bids and the argmax
crates/tinyhivemind-hive/src/episode/	the state machine and the visibility filter
crates/tinyhivemind-hive/examples/bench/	the benchmark harness
docs/adr/	architecture decision records
docs/specs/	behavior specifications
ROADMAP.md	the phase plan and the two defects it fixes