Iterated Belief Change in Multi-Agent Systems (original) (raw)

A model for belief revision in a multi-agent environment (abstract

ACM Sigois Bulletin, 1992

In modeling the knowledge processing structure of an Agent in a Multi-Agent world it becomes necessary to enlarge the traditional concept of Belief Revision. For detecting contradictions and identifying their sources it is sufficient to maintain informations about what has been told; but to "solve" a contradiction it is necessary to keep informations about who said it or, in general, about the source where that knowledge came from. We can take as certain the fact that an agent gave an information, but we can take the given information only as a revisable assumption. The Belief Revision system can't leave the sources of the informations out of consideration because of their relevance in giving the additional notion of "strength of belief" [Galliers 89]. In fact, the reliability of the source affects the credibility of the information and vice-versa. It is necessary to develop systems that deal with couples <assumption, source of the assumption>. In [Dragoni 91] we've proposed a system that moves in this direction. Here we give a short description of that system. In the first two parts we describe the agent's knowledge processing structure using a particular characterization of the "Assumption Based Belief Revision" concept; in part three we outline the project of an embedded device that enables the overall system to deal with couples <assumption, source of the assumption> in an rather anthropomorphic manner.

A MODEL FOR BELIEF REVISION IN A MULTI-AGENT ENVIRONMENT

Dynamic Logics of Belief Change

2015

This chapter gives an overview of current dynamic logics that describe belief update and revision, both for single agents and in multi-agent settings. We employ a mixture of ideas from AGM belief revision theory and dynamic-epistemic logics of information-driven agency. After describing the basic background, we review logics of various kinds of beliefs based on plausibility models, and then go on to various sorts of belief change engendered by changes in current models through hard and soft information. We present matching complete logics with dynamic-epistemic recursion axioms, and develop a very general perspective on belief change by the use of event models and priority update. The chapter continues with three topics that naturally complement the setting of single steps of belief change: connections with probabilistic approaches to belief change, long-term temporal process structure including links with formal learning theory, and multi-agent scenarios of information flow and belief revision in games and social networks. We end with a discussion of alternative approaches, further directions, and windows to the broader literature, while links with relevant philosophical traditions are discussed throughout.

Belief revision through the belief-function formalism in a multi-agent environment

The abilities of detecting contradictions and rearranging the cognitive space in order to cope with them are important to be embedded in the BDI architecture of an agent acting in a complex and dynamic world. However, to be accomplished in a multi-agent environment, “belief revision” must depart considerably from its original definitions. According to us, the main changes should be the following ones: replacing the “priority to the incoming information principle” with the “recoverability principle”: any previously believed piece of information must belong to the current cognitive state whenever it is possible dealing not just with pieces of information but with couples <source, information> since the reliability of the source affects the credibility of the information and vice-versa. The “belief-function” formalism is here accepted as a simple and intuitive way to transfer the sources' reliability to the information's credibility.

(Dis) belief change based on messages processing

2005

This paper focuses on the features of belief change when agents have to consider information received from other agents. We focus on belief change operators when agents have to process messages about a static world. We propose to consider agents' belief state as a set of pairs belief, origin of the belief combined with a preference relation over the agents embedded in the multi-agent system. The belief revision procedure for handling received messages is a safe base revision procedure where messages are considered in their syntactic form. According to the reliability of the sources of the conflicting belief, agents remove the less reliable belief in order to handle the received message. Notice that the less reliable source can be the sender of the message itself. In order not to loose precious information conflicting belief are not removed but considered as potential belief. As the agent changes its belief, potential belief is reconsidered and may be reinstated as current belief. In a similar way, messages can concern statements that should not be believed, called disbelief. As belief, disbelief can become potential. These different kinds of belief enables us to propose a new semantics for a modal based language for describing (dis)belief. Agents may handle sequences of messages since the proposed belief change operators handle iterated belief change.

A logical approach for describing (dis) belief change and message processing

2004

This paper focuses on the features of two KQML performatives, namely tell and untell, in the context of nonprioritized belief change. Tell allows agents to send beliefs while untell allows agents to send explicit disbeliefs. In a multi agent system, agents have to change their belief when they receive new information from other agents. They may revise or contract their belief state accordingly. The revision action consists of inserting a new belief in a beliefs set while the contraction action consists of managing a set of disbeliefs. Whenever incoming information entails inconsistencies in an agent's belief state, the agent must either drop some beliefs or refuse the incoming statement. For this, agents consider a preference relation over other agents embedded in the multi agent system and may reject new information based on their belief state and their preference relation. In this article, we survey a logic-based framework for handling messages and (dis)beliefs change. In this context, we formally describe the consequences of tell and untell performatives.

Handling sequences of belief change in a multi-agent context

2003

This paper focuses on the features of belief change in a multiagent context. Agents have to consider information received from the other agents and the ability of how to change beliefs after receiving a message is a prerequisite for many multi-agents problems. The agents are embedded in an environment where they are communicating and they have to prevent potential internal conflicts in their beliefs. We study the belief change operators in that context. Our approach is to consider that agents' belief state is a set of pairs belief, origin of the belief combined with a preference relation over the agents embedded in the multi-agent system. The belief revision procedure for handling received messages is a syntactic approach which aims at selecting the minimal subsets of the belief base in conflict with the received information and, according to the reliability of the sources of the conflicting beliefs, removing the less reliable beliefs in order to handle the received message. The proposed belief change operators ensure that an agent makes as few changes as possible but also handle iterated belief changes by preserving the order on the beliefs.

Dynamic Belief Revision over Multi-Agent Plausibility Models

2006

In this paper, we develop a notion of doxastic actions, general enough to cover all examples of communication actions and most other belief-changing actions encountered in the literature, but also flexible enough to deal with the issue of (static and dynamic) revision of beliefs. This can be seen as a natural extension of the work in [3, 4] on “epistemic actions”, incorporating ideas from the semantics of belief revision and of conditional belief, along the lines pioneered in [2] and [11], but using the conditional belief approach adopted in [22, 10, 9] and adapted in [25] to the context of dynamic belief revision.

Multi-Agent Belief Revision With Linked Plausibilities

CWI Amsterdam, in Proceedings LOFT VIII, …, 2009

In [11] it is shown how propositional dynamic logic (PDL) can be interpreted as a logic of belief revision that extends the logic of communication and change (LCC) given in [7]. This new version of epistemic/doxastic PDL does not impose any constraints on the basic relations and ...

Iterated Belief Change in Multi-Agent Systems (original) (raw)

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