Handbook of theoretical computer science (vol. B)
Multilanguage hierarchical logics, or: how we can do without modal logics
Artificial Intelligence
Representing and executing agent-based systems
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Local models semantics, or contextual reasoning = locality + compatibility
Artificial Intelligence
The abc of rational agent modelling
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Implementing BDI-like systems by direct execution
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Programming resource-bounded deliberative agents
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Multi-Agent Systems Specification and Certification: A Situation and State Calculus Approach
Annals of Mathematics and Artificial Intelligence
Formalising theories of trust for authentication protocols
Information Systems Frontiers
Exploring the Future with Resource-Bounded Agents
Journal of Logic, Language and Information
Executable specifications of resource-bounded agents
Autonomous Agents and Multi-Agent Systems
ProMAS'05 Proceedings of the Third international conference on Programming Multi-Agent Systems
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In this chapter we introduce a common framework for both the logical specification and execution of agents. This logical framework provides the basis for the specification and execution of agents comprising dynamic (temporal) activity, deliberation concerning goals, and reasoning about belief.We here focus in particular on the ability of this approach to capture an important aspect of practical agents, notably their resource-bounded nature. We present a logic in which resource-boundedness can be specified both in terms of temporal reasoning, and reasoning about belief. Then we consider how specifications within this logic can be directly executed. The mechanism we use to capture finite resources in reasoning about beliefs is to employ a multi-context representation of belief, thus providing tight control over the agent's reasoning capabilities where necessary. The mechanism we use to capture finite resources in temporal reasoning is to use a linear time temporal logic with both finite past and finite future.