Mapping Mental States into Propositional Planning

Felipe Meneguzzi

doi:10.1109/AAMAS.2004.167

Mapping Mental States into Propositional Planning

Felipe Meneguzzi

Computing Science

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Abstract

Most BDI agent architectures rely on plan libraries in order to ensure bounded time for means-ends reasoning. Nevertheless, the usage of fast planning algorithms to provide the agent with runtime planning capabilities is an alternate approach to augment agent autonomy and flexibility. This paper proposes an autonomous agent architecture based on the integration of a logic-based BDI model with propositional planning algorithms through a mapping process.

Original language	English
Title of host publication	Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems
Pages	1514-1515
Volume	4
DOIs	https://doi.org/10.1109/AAMAS.2004.167
Publication status	Published - 2004

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10.1109/AAMAS.2004.167

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title = "Mapping Mental States into Propositional Planning",

abstract = "Most BDI agent architectures rely on plan libraries in order to ensure bounded time for means-ends reasoning. Nevertheless, the usage of fast planning algorithms to provide the agent with runtime planning capabilities is an alternate approach to augment agent autonomy and flexibility. This paper proposes an autonomous agent architecture based on the integration of a logic-based BDI model with propositional planning algorithms through a mapping process.",

author = "Felipe Meneguzzi",

year = "2004",

doi = "10.1109/AAMAS.2004.167",

language = "English",

volume = "4",

pages = "1514--1515",

booktitle = "Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems",

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T1 - Mapping Mental States into Propositional Planning

AU - Meneguzzi, Felipe

PY - 2004

Y1 - 2004

N2 - Most BDI agent architectures rely on plan libraries in order to ensure bounded time for means-ends reasoning. Nevertheless, the usage of fast planning algorithms to provide the agent with runtime planning capabilities is an alternate approach to augment agent autonomy and flexibility. This paper proposes an autonomous agent architecture based on the integration of a logic-based BDI model with propositional planning algorithms through a mapping process.

AB - Most BDI agent architectures rely on plan libraries in order to ensure bounded time for means-ends reasoning. Nevertheless, the usage of fast planning algorithms to provide the agent with runtime planning capabilities is an alternate approach to augment agent autonomy and flexibility. This paper proposes an autonomous agent architecture based on the integration of a logic-based BDI model with propositional planning algorithms through a mapping process.

U2 - 10.1109/AAMAS.2004.167

DO - 10.1109/AAMAS.2004.167

M3 - Published conference contribution

VL - 4

SP - 1514

EP - 1515

BT - Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems

ER -

Mapping Mental States into Propositional Planning

Abstract

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