Conference Proceeding

Computationally Grounded Account of Belief and Awareness for AI Agents.

01/2010; In proceeding of: Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010), Lyon, France, August 30 - September 2, 2010
Source: DBLP
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    ABSTRACT: We have developed a set of tools to allow the use of model-checking techniques for the verification of systems directly implemented in an agent-oriented programming language. The success of model checking as a verification technique for large systems is dependent partly on its use in combination with various state-space reduction techniques. An important example of such techniques is property-based slicing. This paper introduces an algorithm for propertybased slicing of AgentSpeak multi-agent systems. We apply our approach to the AgentSpeak code for a scenario inspired by routine tasks of autonomous Mars rovers, and explain how slicing reduces the search space in theory. We consider experiments on such scenarios, and initial results show a significant reduction in the state space, thus indicating that this approach can have an important impact on the practicality of agent verification.
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    Conference Proceeding: A Logic of Agent Programs.
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    ABSTRACT: We present a sound and complete logic for reasoning about SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementa- tion of cognitive agents with beliefs, goals and plans. Our logic is a variant of PDL, and allows the specification of safety and liveness properties of agent programs. We prove a correspondence between the operational semantics of Sim- pleAPL and the models of the logic for two example program execution strategies. We show how to translate agent pro- grams written in SimpleAPL into expressions of the logic, and give an example in which we show how to verify correct- ness properties for a simple agent program. tional semantics for two example program execution strate- gies. We then give the syntax and semantics of the logic and its sound and complete axiomatization and prove a corre- spondencebetweentheoperationalsemanticsofSimpleAPL and the models of the logic for both program execution strategies. Finally, we show how to translate agent programs written in SimpleAPL into expressionsof the logic, and give an example in which we verify correctness properties of a simple agent program using a theorem prover.
    Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, July 22-26, 2007, Vancouver, British Columbia, Canada; 01/2007
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    ABSTRACT: This paper explores principles governing the rational balance among an agent's beliefs, goals, actions, and intentions. Such principles provide specifications for artificial agents, and approximate a theory of human action (as philosophers use the term). By making explicit the conditions under which an agent can drop his goals, i.e., by specifying how the agent is committed to his goals, the formalism captures a number of important properties of intention. Specifically, the formalism provides analyses for Bratman's three characteristic functional roles played by intentions [7, 9], and shows how agents can avoid intending all the foreseen side-effects of what they actually intend. Finally, the analysis shows how intentions can be adopted relative to a background of relevant beliefs and other intentions or goals. By relativizing one agent's intentions in terms of beliefs about another agent's intentions (or beliefs), we derive a preliminary account of interpersonal commitments.
    Artif. Intell. 01/1990; 42:213-261.


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Natasha Alechina