Dealing with Incompatibilities among Procedural Goals under Uncertainty

By considering rational agents, we focus on the problem of selecting goals out of a set of incompatible ones. We consider three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal, the instrumental (or based on resources), and the superfluity. We represent the agent's plans by means of structured arguments whose premises are pervaded with uncertainty. We measure the strength of these arguments in order to determine the set of compatible goals. We propose two novel ways for calculating the strength of these arguments, depending on the kind of incompatibility that exists between them. The first one is the logical strength value, it is denoted by a three-dimensional vector, which is calculated from a probabilistic interval associated with each argument. The vector represents the precision of the interval, the location of it, and the combination of precision and location. This type of representation and treatment of the strength of a structured argument has not been defined before by the state of the art. The second way for calculating the strength of the argument is based on the cost of the plans (regarding the necessary resources) and the preference of the goals associated with the plans. Considering our novel approach for measuring the strength of structured arguments, we propose a semantics for the selection of plans and goals that is based on Dung's abstract argumentation theory. Finally, we make a theoretical evaluation of our proposal.

[1]  Juan Carlos Nieves,et al.  Smart augmented reality mHealth for medication adherence , 2018, AIH@IJCAI.

[2]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[3]  Michael Schroeder,et al.  Fuzzy Unification and Argumentation for Well-Founded Semantics , 2004, SOFSEM.

[4]  Gurkan Tuna,et al.  An autonomous wireless sensor network deployment system using mobile robots for human existence detection in case of disasters , 2014, Ad Hoc Networks.

[5]  Ulises Cortés,et al.  Modality-based Argumentation Using Possibilistic Stable Models , 2006 .

[6]  Ali A. Alesheikh,et al.  Introducing a novel model of belief-desire-intention agent for urban land use planning , 2013, Eng. Appl. Artif. Intell..

[7]  Henry Prakken,et al.  The ASPIC+ framework for structured argumentation: a tutorial , 2014, Argument Comput..

[8]  Bernard Yannou,et al.  Preventing design conflicts in distributed design systems composed of heterogeneous agents , 2014, Eng. Appl. Artif. Intell..

[9]  Cristiano Castelfranchi,et al.  The role of beliefs in goal dynamics: prolegomena to a constructive theory of intentions , 2007, Synthese.

[10]  A. Senthil Kumar,et al.  Development of a distributed collaborative design framework within peer-to-peer environment , 2008, Comput. Aided Des..

[11]  Anthony Hunter,et al.  A probabilistic approach to modelling uncertain logical arguments , 2013, Int. J. Approx. Reason..

[12]  Gonzalo Pajares,et al.  New Trends in Robotics for Agriculture: Integration and Assessment of a Real Fleet of Robots , 2014, TheScientificWorldJournal.

[13]  Rolf Haenni Probabilistic argumentation , 2009, J. Appl. Log..

[14]  Monica Wachowicz,et al.  A design and application of a multi-agent system for simulation of multi-actor spatial planning. , 2004, Journal of environmental management.

[15]  Niki Pfeifer,et al.  Framing human inference by coherence based probability logic , 2009, J. Appl. Log..

[16]  Daniel Moldt,et al.  Goal Representation for BDI Agent Systems , 2004, PROMAS.

[17]  Iyad Rahwan,et al.  An argumentation based approach for practical reasoning , 2006, AAMAS '06.

[18]  Rafael H. Bordini,et al.  BDI agent programming in AgentSpeak using Jason , 2006 .

[19]  Martin Caminada,et al.  On the evaluation of argumentation formalisms , 2007, Artif. Intell..

[20]  Niki Pfeifer,et al.  Inference in conditional probability logic , 2006, Kybernetika.

[21]  Michael Winikoff,et al.  Rich goal types in agent programming , 2011, AAMAS.

[22]  Leila Amgoud,et al.  A Formal Framework for Handling Conflicting Desires , 2003, ECSQARU.

[23]  Henri Prade,et al.  Using Arguments for Making Decisions: A Possibilistic Logic Approach , 2004, UAI.

[24]  Henri Prade,et al.  Using arguments for making and explaining decisions , 2009, Artif. Intell..

[25]  Marie-Christine Lagasquie-Schiex,et al.  A constrained argumentation system for practical reasoning , 2008, AAMAS.

[26]  Niki Pfeifer,et al.  On Argument Strength , 2013 .

[27]  Thomas Lukasiewicz,et al.  Combining probabilistic logic programming with the power of maximum entropy , 2004, Artif. Intell..

[28]  Camelia Chira,et al.  Multi-agent Support for Distributed Engineering Design , 2005, IEA/AIE.

[29]  Josep Puyol-Gruart,et al.  An argumentation-based approach for identifying and dealing with incompatibilities among procedural goals , 2019, Int. J. Approx. Reason..

[30]  Guillermo Ricardo Simari,et al.  A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge , 2004, UAI.

[31]  Leon van der Torre,et al.  Combining goal generation and planning in an argumentation framework , 2004, NMR.

[32]  A. Davids Urban search and rescue robots: from tragedy to technology , 2002 .

[33]  Guillermo Ricardo Simari,et al.  Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification , 2008, Int. J. Approx. Reason..