Nadim Obeid

Partial information basis for agent-based collaborative dialogue

We propose a partial information state-based framework for collaborative dialogue and argument between agents. We employ a three-valued based nonmonotonic logic, NML3, for representing and reasoning about Partial Information States (PIS). NML3 formalizes some aspects of revisable reasoning and it is sound and complete. Within the framework of NML3, we present a formalization of some basic dialogue moves and the rules of protocols of some types of dialogue. The rules of a protocol are nonmonotonic in the sense that the set of propositions to which an agent is committed and the validity of moves vary from one move to another. The use of PIS allows an agent to expand consistently its viewpoint with some of the propositions to which another agent, involved in a dialogue, is overtly committed. A proof method for the logic NML3 has been successfully implemented as an automatic theorem prover. We show, via some examples, that the tableau method employed to implement the theorem prover allows an agent, absolute access to every stage of a proof process. This access is useful for constructive argumentation and for finding cooperative and/or informative answers.

A Formalism for Representing and Reasoning with Temporal Information, Event and Change

In this paper we present a general formalism for representing and reasoning with temporal information, event and change. The temporal framework is a theory of time that takes both points and interval as temporal primitives and where the base logic is that of Kleene’s three-valued logic. Thus, we can avoid the Divided Instant Problem (DIP). We present a three-valued based Temporal First-Order Nonmonotonic Logic (TFONL) that employs an explicit representation of time and events. We may embody default logic into TFONL, which takes into consideration the frame, qualification and ramification problems.

On integrating event definition and event detection

We develop, in this paper, a representation of time and events that supports a range of reasoning tasks such as monitoring and detection of event patterns which may facilitate the explanation of root cause(s) of faults. We shall compare two approaches to event definition: the active database approach in which events are defined in terms of the conditions for their detection at an instant, and the knowledge representation approach in which events are defined in terms of the conditions for their occurrence over an interval. We shall show the shortcomings of the former definition and employ a three-valued temporal first order nonmonotonic logic, extended with events, in order to integrate both definitions.

Towards a Model of Learning through Communication

Abstract. Communication is an interactive, complex, structured process involving agents that are capable of drawing conclusions from the information they have available about some real-life situations. Such situations are generally characterized as being imperfect. In this paper, we aim to address learning from the perspective of the communication between agents. To learn a collection of propositions concerning some situation is to incorporate it within ones knowledge about that situation. That is, the key factor in this activity is for the goal agent, where agents may switch role if appropriate, to integrate the information offered with what it already knows. This may require a process of belief revision, which suggests that the process of incorporation of new information should be modeled nonmonotonically. We shall employ for reasoning a three-valued based nonmonotonic logic that formalizes some aspects of revisable reasoning and it is accessible to implementation. The logic is sound and complete. A theorem-prover of the logic has successfully been implemented.

Dialogue and Argumentation in Multi-agent Diagnosis

In this paper, we make a first step towards a formal model of dialogue and argumentation for a multi-agent (model-based) diagnostic system. We shall discuss some of the issues in multi-agent cooperative fault diagnosis, the theories of communicating agents and their reasoning capabilities. We propose a Partial Information State (PIS)-based framework for dialogue and argumentation. We shall employ a three-valued based nonmonotonic logic for representing and reasoning about partial information. We show via an example that the system can easily be customized to handle distributed problem-solving tasks.

On formalizing social commitments in dialogue and argumentation models using temporal defeasible logic

In this paper, we take the view that any formalization of commitments has to come together with a formalization of time, events/actions and change. We enrich a suitable formalism for reasoning about time, event/action and change in order to represent and reason about commitments. We employ a three-valued based temporal first-order non-monotonic logic (TFONL) that allows an explicit representation of time and events/action. TFONL subsumes the action languages presented in the literature and takes into consideration the frame, qualification and ramification problems, and incorporates to a domain description the set of rules governing change. It can handle protocols for the different types of dialogues such as information seeking, inquiry and negotiation. We incorporate commitments into TFONL to obtain Com-TFONL. Com-TFONL allows an agent to reason about its commitments and about other agents’ behaviour during a dialogue. Thus, agents can employ social commitments to act on, argue with and reason about during interactions with other agents. Agents may use their reasoning and argumentative capabilities in order to determine the appropriate communicative acts during conversations. Furthermore, Com-TFONL allows for an integration of commitments and arguments which helps in capturing the public aspects of a conversation and the reasoning aspects required in coherent conversations.

Model-Based Diagnosis and Conditional Logic

The model-based diagnostic approach was first introduced to overcome the limitations of heuristic systems. However, research on model-based systems showed that the model-based diagnosis approaches resort to assumptions that can be viewed as the return, though controlled, of heuristics into diagnostic reasoning. In this paper we focus on diagnosis with component-oriented device models. We argue for the need to represent and reason with these assumptions. We present a conditional logic, DL, That is suitable for diagnostic reasoning and allows us to represent and reason with assumptions.

Helpful answers to modal and hypothetical questions

This paper describes a computational pragmatic model which is geared towards providing helpful answers to modal and hypothetical questions. The work brings together elements from formal semantic theories on modality and question answering, defines a wider, pragmatically flavoured, notion of answerhood based on non-monotonic inference and develops a notion of context, within which aspects of more cognitively oriented theories, such as Relevance Theory, can be accommodated. The model has been implemented. The research was funded By ESRC grant number R000231279.

A temporal defeasible logic for handling access control policies

Access control policies are specified within systems to ensure confidentiality of their information. Available knowledge about policies is usually incomplete and uncertain. An essential goal in reasoning is to reach conclusions which can be justified. However, since justification does not necessarily guarantee truth, the best we can do is to derive “plausible/ tentative” conclusions from partial and conflicting information. Policies are typically expressed as rules that could be complex and include timing constraints. Complex sets of access policies can contain conflicts e.g., a rule allows access while another rule prevents it. In this paper, we aim at providing a formalism for specifying authorization policies of a dynamic system. We present a temporal defeasible logic (TDL) which allows us to specify temporal policies and to handle conflicts. It can be shown that the proposed model is a generalization of the role-based access control model.

Towards a Formal Model of Knowledge Sharing in Complex Systems

Knowledge sharing between various components of a system is a prerequisite for a successful knowledge management system. A knowledge sharing model includes providing knowledge workers with the knowledge, experiences and insights which they need to perform their tasks. We propose a multi-agent system that assists in the process of knowledge sharing between concerned knowledge worker groups. Each agent is a knowledge broker and organizer for a specialized knowledge worker group involved in the operations of a sub-system. In addition to timely access to knowledge, it should help in understanding the motivation which underlies decisions made by other groups and/or the information/knowledge bases for such decisions. Each agent is expected to learn about the activities, contexts of decisions, knowledge employed and experiences of other knowledge workers groups whose activities are considered to be relevant to the group it represents. We shall employ Partial Information State (PIS) to represent the knowledge of the agents. We shall employ a three-valued based nonmonotonic logic for reasoning about PISs. We present a multi-agent based model of argumentation and dialogue for knowledge sharing.