Decision theoretic norm-governed planning

Luca Gasparini; Timothy J. Norman; Martin J. Kollingbaum; Liang Chen

Decision theoretic norm-governed planning

Luca Gasparini, Timothy J. Norman, Martin J. Kollingbaum, Liang Chen

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

Abstract

We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.

Original language	English
Title of host publication	AAMAS '16 International Conference on Agents and Multiagent Systems
Place of Publication	Richland, SC
Publisher	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages	1265-1266
Number of pages	2
ISBN (Electronic)	9781450342391
Publication status	Published - 2016
Event	15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore Duration: 9 May 2016 → 13 May 2016

Conference

Conference	15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/Territory	Singapore
City	Singapore
Period	9/05/16 → 13/05/16

Keywords

Coordination
Decision theory
Norms

Cite this

Decision theoretic norm-governed planning. / Gasparini, Luca; Norman, Timothy J.; Kollingbaum, Martin J. et al.
AAMAS '16 International Conference on Agents and Multiagent Systems. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2016. p. 1265-1266.

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

Gasparini, L, Norman, TJ, Kollingbaum, MJ & Chen, L 2016, Decision theoretic norm-governed planning. in AAMAS '16 International Conference on Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), Richland, SC, pp. 1265-1266, 15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016, Singapore, Singapore, 9/05/16.

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abstract = "We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.",

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author = "Luca Gasparini and Norman, {Timothy J.} and Kollingbaum, {Martin J.} and Liang Chen",

year = "2016",

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booktitle = "AAMAS '16 International Conference on Agents and Multiagent Systems",

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AU - Gasparini, Luca

AU - Norman, Timothy J.

AU - Kollingbaum, Martin J.

AU - Chen, Liang

PY - 2016

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N2 - We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.

AB - We propose Normative Dec-POMDPs, a model of collective decision making in the presence of complex norms, with violations of norms classified according to their relative severity. We extend the PBPG algorithm in order to solve Normative Dec-POMDPs and propose a heuristic that improves its scalability without affecting the policy quality.

KW - Coordination

KW - Decision theory

KW - Norms

UR - http://www.scopus.com/inward/record.url?scp=85014135481&partnerID=8YFLogxK

M3 - Published conference contribution

AN - SCOPUS:85014135481

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EP - 1266

BT - AAMAS '16 International Conference on Agents and Multiagent Systems

PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)

CY - Richland, SC

T2 - 15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016

Y2 - 9 May 2016 through 13 May 2016

ER -

Decision theoretic norm-governed planning

Abstract

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Keywords

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