Development of projects for the course "Artificial Intelligence and Laboratory"
The project was carried out for the "Artificial Intelligence and Laboratory" course, from the description on the Turin Department of Computer Science's university page:
The main objective of the course is to provide a deep investigation of Artificial Intelligence, in particular concerning the abilities of an intelligent agent to perform inferences from an explicit knowledge base of a given domain. In addition to methodological skills, also project development skills will be taken into account, since the course comprises the experimentation of automated reasoning mechanisms based on logic programming, as well as the development of an intelligent agent able to exhibit both deliberative and reactive behaviors (by using tools based on production rules) and the use of tools for cognitive architectures.
Project development covers the following topics:
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Automated planning and execution in real world scenarios. Concerning the methodological part, the course will cover the following topics: representation of actions and goals, methods for automatic plan generation.
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Reasoning under uncertainty. The methodological part will cover probabilistic reasoning, Bayesian networks and reasoning mechanisms for Bayesian networks, temporal probabilistic models.
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Implementation of an intelligent agent. This experimental part consists in the development of a proof of concept of an intelligent agent able to exhibit deliberative and reactive behavior in a partially observable environment. The proof of concept will be developed by exploiting facilities offered by CLIPS, a well established and efficient tool based on production rules. The course will show how to develop basic functionalities of problem solving by using the inferential engine of CLIPS.
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Implementation of a reinforcement learning agent controlled by the cognitive architecture SOAR. This experimental part consists in the exploitation and development of a learning agent able to exhibit intelligent behavior based on rewards in a game-like environment. The proof of concept will be developed by using the SOAR cognitive architecture. The course will show how to develop basic functionalities of learning and problem solving in SOAR.