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Partially Observable Markov Decision Processes with Behavioral Norms

Authors: Matthias Nickles and Achim Rettinger

Published in: Dagstuhl Seminar Proceedings, Volume 9121, Normative Multi-Agent Systems (2009)

Abstract

This extended abstract discusses various approaches to the constraining of Partially Observable Markov Decision Processes (POMDPs) using social norms and logical assertions in a dynamic logic framework. Whereas the exploitation of synergies among formal logic on the one hand and stochastic approaches and machine learning on the other is gaining significantly increasing interest since several years, most of the respective approaches fall into the category of relational learning in the widest sense, including inductive (stochastic) logic programming. In contrast, the use of formal knowledge (including knowledge about social norms) for the provision of hard constraints and prior knowledge for some stochastic learning or modeling task is much less frequently approached. Although we do not propose directly implementable technical solutions, it is hoped that this work is a useful contribution to a discussion about the usefulness and feasibility of approaches from norm research and formal logic in the context of stochastic behavioral models, and vice versa.

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Matthias Nickles and Achim Rettinger. Partially Observable Markov Decision Processes with Behavioral Norms. In Normative Multi-Agent Systems. Dagstuhl Seminar Proceedings, Volume 9121, pp. 1-13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{nickles_et_al:DagSemProc.09121.25,
  author =	{Nickles, Matthias and Rettinger, Achim},
  title =	{{Partially Observable Markov Decision Processes with Behavioral Norms}},
  booktitle =	{Normative Multi-Agent Systems},
  pages =	{1--13},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9121},
  editor =	{Guido Boella and Pablo Noriega and Gabriella Pigozzi and Harko Verhagen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09121.25},
  URN =		{urn:nbn:de:0030-drops-19134},
  doi =		{10.4230/DagSemProc.09121.25},
  annote =	{Keywords: Norms, Partially Observable Markov Decision Processes, Deontic Logic, Propositional Dynamic Logic}
}

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DOI: 10.4230/DagSemProc.07122.30

Towards a Logic of Graded Normativity and Norm Adherence

Authors: Matthias Nickles

Published in: Dagstuhl Seminar Proceedings, Volume 7122, Normative Multi-agent Systems (2007)

Abstract

A key focus of contemporary agent-oriented research and engineering is on open multiagent systems composed of truly autonomous, interacting agents. This poses new challenges, as entities in open systems are usually more or less mentally opaque (e.g., possibly insincere), and can enter and leave the system at will. Thus interactions among such black- or gray-box entities usually imply more or less severe contingencies in behavior: Among other issues, in principle, the adherence of agents to norms cannot be guaranteed in such systems. As a response to this issue, this paper proposes a logic-based approach based on the notion of (possibly probabilistic) behavioral expectations, which are stylized either as adaptive (i.e., predictive) or normative (i.e., prescriptive). Some features of this approach are the enabling of "soft norms" which are automatically weakened to some degree if contradicted at runtime, and the possibility to quantify norm adherence using the measurement of norm deviance.

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Matthias Nickles. Towards a Logic of Graded Normativity and Norm Adherence. In Normative Multi-agent Systems. Dagstuhl Seminar Proceedings, Volume 7122, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{nickles:DagSemProc.07122.30,
  author =	{Nickles, Matthias},
  title =	{{Towards a Logic of Graded Normativity and Norm Adherence}},
  booktitle =	{Normative Multi-agent Systems},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7122},
  editor =	{Guido Boella and Leon van der Torre and Harko Verhagen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07122.30},
  URN =		{urn:nbn:de:0030-drops-9267},
  doi =		{10.4230/DagSemProc.07122.30},
  annote =	{Keywords: Computational Norms, Dynamic Logic, Computational Expectations, Social AI}
}

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Documents authored by Nickles, Matthias

Partially Observable Markov Decision Processes with Behavioral Norms

Abstract

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Towards a Logic of Graded Normativity and Norm Adherence

Abstract

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