Browse ORBilu by Open Access
- What it is and what it isn't
- Green Road / Gold Road?
- Ready to Publish. Now What?
- How can I support the OA movement?
- Where can I learn more?
ORBilu is a project developed by
   Rewriting Rules for the Computation of Goal-Oriented Changes in an Argumentation System; ; et al in CLIMA (2013) When several agents are engaged in an argumentation process, they are faced with the problem of deciding how to contribute to the current state of the debate in order to satisfy their own goal, ie. to ... [more ▼] When several agents are engaged in an argumentation process, they are faced with the problem of deciding how to contribute to the current state of the debate in order to satisfy their own goal, ie. to make an argument under a given semantics accepted or not. In this paper, we study the minimal changes (or target sets) on the current state of the debate that are required to achieve such a goal, where changes are the addition and/or deletion of attacks among arguments. We study some properties of these target sets, and propose a Maude specification of rewriting rules which allow to compute all the target sets for some types of goals [less ▲] Detailed reference viewed: 119 (1 UL)Learning and Reasoning about Norms using Neural-Symbolic Systems; ; Colombo Tosatto, Silvano  et alin International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Valencia, Spain, June 4-8, 2012 (2012) In this paper we provide a neural-symbolic framework to model, reason about and learn norms in multi-agent systems. To this purpose, we define a fragment of Input/Output (I/O) logic that can be embedded ... [more ▼] In this paper we provide a neural-symbolic framework to model, reason about and learn norms in multi-agent systems. To this purpose, we define a fragment of Input/Output (I/O) logic that can be embedded into a neural network. We extend d’Avila Garcez et al. Connectionist Inductive Learning and Logic Programming System (CILP) to translate an I/O logic theory into a Neural Network (NN) that can be trained further with examples: we call this new system Normative- CILP (N-CILP). We then present a new algorithm to handle priorities between rules in order to cope with normative issues like Contrary to Duty (CTD), Priorities, Exceptions and Permissions. We illustrate the applicability of the framework on a case study based on RoboCup rules: within this working example, we compare the learning capacity of a network built with N-CILP with a non symbolic neural net- work, we explore how the initial knowledge impacts on the overall performance, and we test the NN capacity of learn- ing norms, generalizing new Contrary to Duty rules from examples. [less ▲] Detailed reference viewed: 129 (0 UL)Multi-sorted ArgumentationRienstra, Tjitze ; ; et alin Proceedings of the 1st International Workshop on the Theory and Applications of Formal Argumentation (TAFA 2011) (2011, July 16), 7132 In the theory of abstract argumentation, the acceptance status of arguments is normally determined for the complete set of arguments at once, under a single semantics. However, this is not always desired ... [more ▼] In the theory of abstract argumentation, the acceptance status of arguments is normally determined for the complete set of arguments at once, under a single semantics. However, this is not always desired. In this paper, we extend the notion of an argumentation framework to a multi-sorted argumentation framework, and we motivate this extension using an example which considers practical and epistemic arguments. In a multi-sorted argumentation framework, the arguments are partitioned into a number of cells, where each cell is associated with a semantics under which its arguments are evaluated. We prove the properties of the proposed framework, and we demonstrate our theory with a number of examples. Finally, we relate our theory to the theory of modal fibring of argumentation networks. [less ▲] Detailed reference viewed: 113 (0 UL)Argumentative Agents Negotiating on Potential Attacks; Gabbay, Dov M. ; et alin KES-AMSTA (2011) When arguing, agents may want to discuss about the details after agreeing about the general problems. We propose to model this kind of situation using an extended argumentation framework with potential ... [more ▼] When arguing, agents may want to discuss about the details after agreeing about the general problems. We propose to model this kind of situation using an extended argumentation framework with potential attacks. Agents negotiation about raising potential attacks or not, in order to maximize the number of their accepted arguments. The result of the negotiation process consists in the formation of coalitions composed by those agents which have found an agreement. The two proposed negotiation protocols have been implemented and an evaluation, addressed by means of experimental results, shows which combination of strategies and negotiation protocol allows the agents to optimize outcomes. [less ▲] Detailed reference viewed: 112 (1 UL)Coalition Formation via Negotiation in Multiagent Systems with Voluntary Attacks; Gabbay, Dov M. ; et alin Proceedings of the 22th Belgian-Netherlands Conference on Artificial Intelligence (BNAIC'10) (2010) Argumentation networks are put forward by Dung considering only one kind of attack among argu- ments. In this paper, we propose to extend Dung’s argumentation framework with voluntary attacks in the ... [more ▼] Argumentation networks are put forward by Dung considering only one kind of attack among argu- ments. In this paper, we propose to extend Dung’s argumentation framework with voluntary attacks in the context of multiagent systems, characterized by the possibility of the attacker to decide whether to attack or not. Enabling voluntary attacks impacts on the acceptability of the arguments in the framework, and therefore it becomes subject of debate between the agents. Agents can negotiate about which subset of voluntary attacks can be raised, and they form coalitions after the negotiation process. [less ▲] Detailed reference viewed: 22 (1 UL) |
||
