Abstract:
In this thesis we study a reasoning module for agents that have cognitive abilities, such as memory, perception, action, and are expected to function autonomously for long periods of time. The module provides the ability to reason about action and change using the language of the situation calculus and variants of the basic action theories. The main focus of this thesis is on the logical problem of progressing an action theory.

First, we investigate the conjecture by Lin and Reiter that a practical first-order
definition of progression is not appropriate for the general case. We show that Lin and Reiter were indeed correct in their intuitions by providing a proof for the conjecture, thus resolving the open question about the first-order definability of progression and justifying the need for a second-order definition.

Then we proceed to identify three cases where it is possible to obtain a first-order progression with the desired properties: i) we extend earlier work by Lin and Reiter and present a case where we restrict our attention to a practical class of queries that may only quantify over situations in a limited way; ii) we revisit the local-effect assumption of Liu and Levesque that requires that the effects of an action are fixed by the arguments of the action and show that in this case a first-order progression is suitable; iii) we investigate a way that the local-effect assumption can be relaxed and show that when the initial knowledge base is a database of possible closures and the effects of the actions are range-restricted then a first-order progression is also suitable under a just-in-time assumption.

Finally, we examine a special case of the action theories with range-restricted effects and present an algorithm for computing a finite progression. We prove the correctness and the complexity of the algorithm, and show its application in a simple example that is inspired by video games.

Bibtex:

@phdthesis{vassos09phdthesis,
address = {Toronto, Canada},
author = {Vassos, Stavros},
school = {University of Toronto},
title = {A Reasoning Module for Long-Lived Cognitive Agents},
year = {2009}
}

Bibtex:

@inproceedings{vassos09rangerestricted,
address = {Toronto, Canada},
author = {Vassos, Stavros and Sardina, Stavros and Levesque, Hector},
booktitle = {Proceedings of the Ninth International Symposium on Logical Formalizations of Commonsense Reasoning (CS-09)},
editor = {Lakemeyer, Gerhard and Morgenstern, Leora and Williams, Mary-Anne},
pages = {135–140},
publisher = {UTSePress},
title = {Progressing basic action theories with non-local effect actions},
year = {2009}
}

Bibtex:

@inproceedings{vassos09localeffect,
address = {Sydney, Australia},
author = {Vassos, Stavros and Lakemeyer, Gerhard and Levesque, Hector},
booktitle = {Proceedings of 11th International Conference on Principles of Knowledge Representation and Reasoning (KR-08)},
editor = {Brewka, Gerhard and Lang, J{\’{e}}r{\^{o}}me},
pages = {662–672},
publisher = {AAAI Press},
title = {First-Order Strong Progression for Local-Effect Basic Action Theories},
year = {2009}
}

Dear Stavros and Hector,

On behalf of the Association for the Advancement of Artificial Intelligence and the AAAI-08 Program Committee, we are pleased to inform you that your paper, entitled “On the Progression of Situation Calculus Basic Action Theories: Resolving a 10-year-old Conjecture,” has been selected for Honorable Mention at AAAI-08.

Each year AAAI’s Conference on Artificial Intelligence honors papers that exemplify high standards in technical contribution and exposition. Papers were recommended for this status by members of the Program Committee during the blind review process. The winning papers were selected by the Program Chairs with the help of some members of the Senior Program Committee.

In recognition of your achievement, you and your coauthors will be presented with certificates by the AAAI-08 Program Cochairs, Dieter Fox and Carla Gomes, during their opening remarks on Tuesday, July 15, at 8:30 am. There will also be an announcement of this honor in the front matter of the AAAI-08 Proceedings.
[...]

More on the paper here and more on the award here.

Abstract:

In this paper, we propose a new progression mechanism for a restricted form of incomplete knowledge formulated as a basic action theory in the situation calculus. Specifically, we focus on functional fluents and deal directly with the possible values these fluents may have and how these values are affected by both physical and sensing actions. The method we propose is logically complete and can be calculated efficiently using database techniques under certain reasonable assumptions.

Bibtex:

@inproceedings{vassos07progression,
title = {Progression of Situation Calculus Action Theories with Incomplete Information},
author = {Vassos, Stavros and Levesque, Hector },
booktitle = {Proceedings of the 20th International Joint Conference on Artificial Intelligence},
editor = {Veloso, Manuela M. },
pages = {2024–2029},
address = {Hyderabad, India},
citeulike-article-id = {1923630},
keywords = {ai, progression, reasoning_about_action, situation_calculus},
month = {January},
year = {2007}
}

Abstract:

This paper describes an implementation of the the Wumpus World in IndiGolog with the objective of showing the applicability of this interleaved agent programming language for modeling agent behavior in realistic domains. We briefly go over the IndiGolog architecture, explain how we can reason about the Wumpus World domain, and show how to express agent behavior using high-level agent programs. Finally, we discuss initial empirical results obtained as well as challenging issues to be resolved.

Bibtex:

@inproceedings{sardina05wumpus,
title = {The {W}umpus {W}orld in {I}ndi{G}olog: {A} {P}reliminary {R}eport},
author = {Sardina, Sebastian and Vassos, Stavros },
booktitle = {In Proceedings the Nonmonotonic Reasoning,
Action and Change Workshop at IJCAI (NRAC-05)},
address = {Edinburgh, Scotland},
pages = {90–95},
citeulike-article-id = {381288},
keywords = {agent, ai, cogrobo, games, golog, incomplete_knowledge, logic, reasoning_about_action, situation_calculus, system, wumpus},
year = {2005}
}

Abstract:
In this thesis we present Lp, a reinterpretation of situation calculus based on intuitions from many-valued logics. The key difference is that the notion of truth is based on the fact that a term is interpreted into a set of objects rather than one single object and equality is interpreted as “possibly equals”. Lp is suitable for defining action theories that capture fluent-based disjunctive knowledge, which means that any incomplete knowledge the theory captures is limited to be about the value of one fluent each time. This essentially enforces an independence assumption on the fluents which allows for efficient evaluation mechanisms. We show that like situation calculus a similar regression theorem holds in Lp. Furthermore, we prove that Lp can be embedded in situation calculus and show how a special form of Lp theories can be soundly implemented in Prolog and the agent programming language Indigolog.

Bibtex:

@mastersthesis{vassos05msthesis,
title = {A Feasible Approach to Disjunctive Knowledge in Situation Calculus},
author = {Vassos, Stavros },
editor = {Levesque, Hector and Bacchus, Fahiem },
school = {University of Toronto},
citeulike-article-id = {2032867},
keywords = {ai, incomplete_knowledge, reasoning_about_action, situation_calculus},
year = {2005}
}

Abstract:
The thesis is a survey of logical nonmonotonic techniques for the solution of the frame problem in artificial intelligence. The approaches are grouped in two main categories, namely those based on minimal change and those based on causality.

Bibtex:

@mastersthesis{vassos01dthesis,
author = {Vassos, Stavros },
citeulike-article-id = {2223905},
editor = {Zachos, E. },
school = {National Technical University of Athens},
title = {Nonmonotonic Logical Approaches for the Frame Problem in Artificial Intelligence},
year = {2001}
}