Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Agents: from direct manipulation to delegation
Software agents
Agent memory and adaptation in multi-agent systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
A BDI Agent Architecture for Dialogue Modelling and Coordination in a Smart Personal Assistant
IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Retrieval, reuse, revision and retention in case-based reasoning
The Knowledge Engineering Review
IHM 2004 Proceedings of the 16th conference on Association Francophone d'Interaction Homme-Machine
An aggregation procedure for building episodic memory
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
CMRadar: a personal assistant agent for calendar management
AOIS'04 Proceedings of the 6th international conference on Agent-Oriented Information Systems II
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We consider Personal Assistant PA agents as cognitive agents capable of helping users handle tasks at their workplace. A PA must communicate with the user using casual language, sub-contract the requested tasks, and present the results in a timely fashion. This leads to fairly complex cognitive agents. However, in addition, such an agent should learn from previous tasks or exchanges, which will increase its complexity. Learning requires a memory, which leads to the two following questions: Is it possible to design and build a generic model of memory? If it is, is it worth the trouble? The article tries to answer the questions by presenting the design and implementation of a memory for PA agents, using a case approach, which results in an improved agent model called MemoPA.