Artificial Intelligence - Special issue on knowledge representation
Planning and acting in partially observable stochastic domains
Artificial Intelligence
Intention reconsideration in complex environments
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Reasoning about rational agents
Reasoning about rational agents
Meta-Level Architectures and Reflection
Meta-Level Architectures and Reflection
The Computational Complexity of Agent Design Problems
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
On Partially Observable MDPs and BDI Models
Selected papers from the UKMAS Workshop on Foundations and Applications of Multi-Agent Systems
Reasoning about Intentions in Uncertain Domains
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Design principles for heavy intelligent agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Metacognition in computation: a selected research review
Artificial Intelligence
On the relationship between MDPs and the BDI architecture
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Comparative analysis of frameworks for knowledge-intensive intelligent agents
AI Magazine - Special issue on achieving human-level AI through integrated systems and research
An architectural approach to ensuring consistency in hierarchical execution
Journal of Artificial Intelligence Research
Field review: Metacognition in computation: A selected research review
Artificial Intelligence
A comparison of agent decommitment techniques in a real-time environment
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Towards opportunistic action selection in human-robot cooperation
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
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We present a framework that enables a belief-desire-intention (\acro{bdi}) agent to dynamically choose its intention reconsideration policy in order to perform optimally in accordance with the current state of the environment. Our framework integrates an abstract \acro{bdi} agent architecture with the decision theoretic model for discrete deliberation scheduling of Russell and Wefald. As intention reconsideration determines an agent's commitment to its plans, this work increases the level of autonomy in agents, as it pushes the choice of commitment level from design-time to run-time. This makes it possible for an agent to operate effectively in dynamic and open environments, whose behaviour is not known at design time. Following a precise formal definition of the framework, we present an empirical analysis that evaluates the run-time policy in comparison with design-time policies. We show that an agent utilising our framework outperforms agents with fixed policies.