A flexible framework for defeasible logics

Logics for knowledge representation suffer from over-specialization: while each logic may provide an ideal representation formalism for some problems, it is less than optimal for others. A solution to this problem is to choose from several logics and, when necessary, combine the representations. In general, such an approach results in a very difficult problem of combination. However, if we can choose the logics from a uniform framework then the problem of combining them is greatly simplified. In this paper, we develop such a framework for defeasible logics. It supports all defeasible logics that satisfy a strong negation principle. We use logic meta-programs as the basis for the framework.Comment: Proceedings of 8th International Workshop on Non-Monotonic Reasoning, April 9-11, 2000, Breckenridge, Colorad

A Computational Framework for Non-Monotonic Agency, Institutionalised Power and Multi-Agent Systems

This work provides a first computational framework to capture some of the theoretical intuitions developed by the present authors and other colleagues. More precisely, in this paper we propose a computationally oriented model of institutional agency based on Defeasible Logic. The focus here is on the notions of counts-as link and on those of attempt and of personal and direct action to realise states of affairs

Efficient representation and effective reasoning for multi-agent systems

In multi-agent systems, interactions between agents are often related to cooperation or competition in such a fashion that they can fulfil their tasks. Successful interactions often require agents to share common and unified knowledge about their working environment. However, autonomous agents observe and judge their surroundings by their own view. Consequently, agents possibly have partial and sometimes conflicting descriptions of the world. In scenarios where they have to coordinate, they are required to identify the shared knowledge in the group and to be able to reason with available information. This problem requires more sophisticated modelling and reasoning methods, which is beyond the classical logics and monotonic reasoning. We introduce a formal framework based on Defeasible Logic (DL) to describe the knowledge commonly shared by agents, and that obtained from other agents. This enables an agent to efficiently reason about the environment and intentions of other agents given available information. We propose to extend the reasoning mechanism of DL with the superior knowledge. This mechanism allows an agent to integrate its mental attitude with a more trustworthy source of information such as the knowledge shared by the majority of other agents

Modelling Contracts Using RuleML

This paper presents an approach for the specification and implementation of e-contracts for Web monitoring. This is done in the setting of RuleML. We argue that monitoring contract execution requires also a logical account of deontic concepts and of violations. Accordingly, RuleML is extended to cover these aspects

Agents adapt to majority behaviours

Agents within a group can have different perceptions of their working environment and autonomously fulfil their goals. However, they can be aware of beliefs and goals of the group as well as other members so that they can adjust their behaviours accordingly. To model these agents, we explicitly include knowledge commonly shared by the group and that obtained from other agents. By avoiding actions which violate ``mental attitudes'' shared by the majority of the group, agents demonstrate their social commitment to the group. Defeasible logic is chosen as our representation formalism for its computational efficiency, and for its ability to handle incomplete and conflicting information. Hence, our agents can enjoy the low computational cost while performing ``reasoning about others''. Finally, we present the implementation of our multi-agent system

A Defeasible Logic of Policy-based Intention

Most of the theories on formalising intention interpret it as a unary modal operator in Kripkean semantics, which gives it a monotonic look. We argue that policy-based intentions exhibit non-monotonic behaviour which could be captured through a non-monotonic system like defeasible logic. The proposed technique alleviates most of the problems related to logical omniscience

A Semantic Web Based Architecture for e-Contracts in Defeasible Logic

We introduce the DR-CONTRACT architecture to represent and reason on e-Contracts. The architecture extends the DR-device architecture by a deontic defeasible logic of violation. We motivate the choice for the logic and we show how to extend RuleML to capture the notions relevant to describe e-contracts for a monitoring perspective in Defeasible Logic