Towards a general theory of action and time
Artificial Intelligence
“Sometimes” and “not never” revisited: on branching versus linear time temporal logic
Journal of the ACM (JACM) - The MIT Press scientific computation series
Temporal logic and computer science: an overview
Temporal logics and their applications
Modal and temporal logic programming
Temporal logics and their applications
Intention is choice with commitment
Artificial Intelligence
JAM: a BDI-theoretic mobile agent architecture
Proceedings of the third annual conference on Autonomous Agents
A Formal Specification of dMARS
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
Structuring BDI Agents in Functional Clusters
ATAL '99 6th International Workshop on Intelligent Agents VI, Agent Theories, Architectures, and Languages (ATAL),
Testing an Implementation of a Temporal Logic Language
SCCC '00 Proceedings of the XX International Conference of the Chilean Computer Science Society
A real-time architecture for time-aware agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Innovations in intelligent agents
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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The philosophical roots of the Belief-Desire-Intention model lie in Bratman's formulation of an intention theory of planning, in which he sought to make sense of the notion of future-directed intention. Implementations of BDI mainly follow the original Procedural Reasoning System model. BDI has a sound logical basis, exemplified by the Logic Of Rational Agents. While the LORA formulation has a temporal logic component, however, this does not translate into any ability for the agent to reason about actual time. Being able to reason about actual time would bring significant benefits for BDI agents, such as the ability for agents to communicate deadlines and to plan and schedule activities in a cooperating group. Given a suitable representation of temporal knowledge, an agent could learn about the temporal aspects of its own actions and processes, and this knowledge could be used as input to the planning process. This paper outlines a possible implementation strategy for the representation of, and the capacity to reason about, actual time.