Most of the papers of the Cognitive Robotics Group at UofT can be found here.

2004

On Ability to Autonomously Execute Agent Programs with Sensing, with Giuseppe De Giacomo, Yves Lesperance, and Hector J. Levesque. Proceedings of the 4th International Workshop on Cognitive Robotics (CogRobo-04). pp. 88-93. Valencia, Spain. August, 2004. (This is an improved version of the one appearing at PROMAS-03, Melbourne, Australia, July, 2003) [slides here)]

Most existing work in agent programming assumes an execution model where an agent has a knowledge base (KB) about the current state of the world, and makes decisions about what to do in terms of what is entailed or consistent with this KB. Planning then involves looking ahead and gauging what would be consistent or entailed at various stages by possible future KBs. We show that in the presence of sensing, such a model does not always work properly, and propose an alternative that does. We then discuss how this affects agent programming language design/semantics.

On the Semantics of Deliberation in IndiGolog: From Theory to Implementation. with Giuseppe De Giacomo, Yves Lesperance, and Hector J. Levesque. Annals of Mathematics and Artificial Intelligence, 41(2-4):259-299, Aug 2004. (Previous version appeared in Proc. of KR-2002)

2003

Rational Action in Agent Programs with Prioritized Goals. with Steven Shapiro. Proceedings of Autonomous Agents and Multi-Agent Systems Conference (AAMAS-2003), pp. 417-424. Melbourne, Australia. July, 2003. [slides here]

Agent theories and agent programs are two very different styles of specification of agent behavior. The former are declarative in nature, while the latter have an imperative flavor. In this paper, we combine ideas from both areas, yielding a powerful mode of agent specification that also gives the specifier a good deal of control over the complexity of the specified agent. In particular, we extend Shapiro et al.'s \cite{Shapiro95} agent theory to handle prioritized goals and then integrate it with the IndiGolog agent programming language. The result is a new IndiGolog construct that transforms a given nondeterministic, concurrent program $\delta$ into a new program $\delta'$ that can be described as a rational implementation of the original program, in the sense that $\delta'$ is an implementation of $\delta$, and furthermore, $\delta'$ is the most rational of all implementations of $\delta$ relative to a given set of prioritized goals and the agent's knowledge. With this construct, we can specify an agent that will attempt to achieve as many goals as possible in priority order even if the agent does not know of a plan that is guaranteed to achieve all the goals. In this case, the agent will select a plan that she thinks has the best chance of achieving the goals.

On Deliberation under Incomplete Information and the Inadequacy of Entailment and Consistency-Based Formalizations. with Giuseppe De Giacomo, Yves Lesperance, and Hector J. Levesque. In Proceedings of the 1st Programming Multiagent System Languages, Frameworks, Techniques and Tools Workshop (PROMAS-03). Melbourne, Australia. July, 2003.

2002

On the Semantics of Deliberation in IndiGolog: From Theory to Implementation. with Giuseppe De Giacomo, Yves Lesperance, and Hector J. Levesque. In D. Fensel, F. Giunchiglia, D. McGuiness, and M.-A. Williams (Eds.), Principles of Knowledge Representation and Reasoning, Proc. of the 8th Int. Conf. (KR2002), Toulouse, France, April 22-25, 2002, 603-614, Morgan Kaufmann, 2002.

In this paper, we develop an account of the kind of deliberation that an agent that is doing planning or executing high-level programs under incomplete information must be able to perform. The deliberator's job is to produce a kind of plan that does not itself require deliberation to interpret. We characterize these as epistemically feasible programs: programs for which the executing agent, at every stage of execution, by virtue of what it knew initially and the subsequent readings of its sensors, always knows what step to take next towards the goal of
completing the entire program. We formalize this notion and characterize deliberation in the IndiGolog agent language in terms of it. We also show that for certain classes of problems, which correspond to conformant planning and conditional planning, the search for epistemically feasible programs can be limited to programs of a simple syntactic form. We alsodiscuss implementation issues and execution monitoring and replanning.

2001

Local Conditional High-Level Robot Programs (extended version). Extended version of the one appearing in Logic for Programming, Artificial Intelligence and Reasoning (LPAR-01). LNAI 2250, 110-124. La Habana, December 2001. [slides here]

• When it comes to building robot controllers, high-level programming arisesas a feasible alternative to planning. The task then is to verify a high-level program by finding a legal execution of it. However, interleaving offline verification with execution in the world seems to be the most practical approach for large programs and complex scenarios involving information gathering and exogenous events. In this paper, we present a mechanism for performing local lookahead forthe Golog family of high-level robot programs. The main features of such mechanism are that it takes sensing seriously by constructing conditional plans that are ready to be executed in the world, and it mixes perfectly with an account of interleaved perception, planning, and action. Also, a simple implementation is developed.

Executing Guarded Action Theories. with Giuseppe De Giacomo and Hector Levesque. ACM Transactions on Computational Logic (TOCL) 4(2), 495-525, October 2001.

• When it comes to building controllers for robots or agents, high-level programming languages like Golog and ConGolog offer a useful compromise between planning-based approaches and low-level robot programming. However, two serious problems typically emerge in practical implementations of these languages: how to evaluate tests in a program efficiently enough in an open-world setting, and how to make appropriate nondeterministic choices while avoiding full lookahead. Recent proposals in the literature suggest that one could tackle the first problem by exploiting sensing information, and tackle the second by specifying the amount of lookahead allowed explicitly in the program. In this paper, we combine these two ideas and demonstrate their power by presenting an interpreter, written in Prolog, for a variant of Golog that is suitable for efficiently operating in open-world setting by exploiting sensing and bounded lookahead.

Local Conditional High-Level Robot Programs. Workshop on Nonmonotonic Reasoning, Action, and Change at IJCAI-01 (NRAC-01). 64-69. August 2001. Seattle, USA. (This a preliminary version of the one appearing in LPAR-2001). [slide here]

2000

IndiGolog: Execution of Guarded Action Theories. Master's Thesis. Supervisor: Hector J. Levesque. Deparment of Computer Science, University of Toronto, 2000.

For any comment or question, please send me an email to ssardina at cs. toronto.edu
Last update of this page: September 2004