On Fibring Semantics for BDI Logics

This study examines BDI logics in the context of Gabbay's fibring semantics. We show that dovetailing (a special form of fibring) can be adopted as a semantic methodology to combine BDI logics. We develop a set of interaction axioms that can capture static as well as dynamic aspects of the mental states in BDI systems, using Catach's incestual schema G^[a, b, c, d]. Further we exemplify the constraints required on fibring function to capture the semantics of interactions among modalities. The advantages of having a fibred approach is discussed in the final section

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

Logic-Based Specification Languages for Intelligent Software Agents

The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

Information sharing among ideal agents

Multi-agent systems operating in complex domains crucially require agents to interact with each other. An important result of this interaction is that some of the private knowledge of the agents is being shared in the group of agents. This thesis investigates the theme of knowledge sharing from a theoretical point of view by means of the formal tools provided by modal logic. More specifically this thesis addresses the following three points. First, the case of hypercube systems, a special class of interpreted systems as defined by Halpern and colleagues, is analysed in full detail. It is here proven that the logic S5WDn constitutes a sound and complete axiomatisation for hypercube systems. This logic, an extension of the modal system S5n commonly used to represent knowledge of a multi-agent system, regulates how knowledge is being shared among agents modelled by hypercube systems. The logic S5WDn is proven to be decidable. Hypercube systems are proven to be synchronous agents with perfect recall that communicate only by broadcasting, in separate work jointly with Ron van der Meyden not fully reported in this thesis. Second, it is argued that a full spectrum of degrees of knowledge sharing can be present in any multi-agent system, with no sharing and full sharing at the extremes. This theme is investigated axiomatically and a range of logics representing a particular class of knowledge sharing between two agents is presented. All the logics but two in this spectrum are proven complete by standard canonicity proofs. We conjecture that these two remaining logics are not canonical and it is an open problem whether or not they are complete. Third, following a influential position paper by Halpern and Moses, the idea of refining and checking of knowledge structures in multi-agent systems is investigated. It is shown that, Kripke models, the standard semantic tools for this analysis are not adequate and an alternative notion, Kripke trees, is put forward. An algorithm for refining and checking Kripke trees is presented and its major properties investigated. The algorithm succeeds in solving the famous muddy-children puzzle, in which agents communicate and reason about each other's knowledge. The thesis concludes by discussing the extent to which combining logics, a promising new area in pure logic, can provide a significant boost in research for epistemic and other theories for multi-agent systems

Logics of knowledge and action: critical analysis and challenges

International audienceWe overview the most prominent logics of knowledge and action that were proposed and studied in the multiagent systems literature. We classify them according to these two dimensions, knowledge and action, and moreover introduce a distinction between individual knowledge and group knowledge, and between a nonstrategic an a strategic interpretation of action operators. For each of the logics in our classification we highlight problematic properties. They indicate weaknesses in the design of these logics and call into question their suitability to represent knowledge and reason about it. This leads to a list of research challenges

Agent interaction: abstract approaches to modelling, programming and verifying multi-agent systems

Computer systems and their applications are becoming increasingly more complicated. Modern systems often consist of multiple independent parts (hardware and software), which interact with their environment. Computers communicate with other computers, exchange information with and receive commands from their human users and receive information about their physicalor virtual environment. This high degree of interactivity leadsto an inherently larger degree of complexity, which needs to be managed and controlled. An important means to reduce complexity is abstraction. Abstraction meansfinding intuitive concepts to model the complex reality and leaving outunderlying details. In the field of multi-agent systems, in which the work ofthis thesis fits, anthropomorphic abstractions are oftenused. Anagent is an autonomous piece of software, designed and/or built in terms ofanthropomorphic concepts, which interacts with other agents and its environmentin such a way that it takes into account the dynamic circumstances and strives to achieve its aims. In this thesis, we focus on agent interaction. Starting from different viewpoints in the field ofmulti-agent systems, we introduce a number of new abstract concepts for agentinteraction. A danger of using abstraction is that abstract concepts areintroduced without grounding them in the computational reality. Therefore, wetake care to always relate our abstract notions to lower-level concepts. We start in Chapter 2 by anchoring three already existing and popular agentconcepts, which are belief, desire and intention, in externally observableagent behaviour. We provide criteria which formally describe when behaviour of an agent indicates that the agent has a certainmental state (a belief, desire or intention). These criteria can be used by agents themselves to attribute belief, desire and intention to other agents, onthe basis of observed behaviour. Chapter 3 deals with agent verification. As the complexity of agent systems ishigh, verification of these systems is very difficult. We develop two principleswhich aid in making verification of agent systems more manageable. The firstprinciple is language abstraction. We use two logical languages to phraseproperties, an abstract one and a detailed one. Properties in theabstract language are shorter and more intuitive than properties in thedetailed language. The second principle is constructing abstract, generic,reusable systems of properties and proofs. In Chapter 4 we present a new model of agents, which focuses on agentinteraction. Our model explicitly includes the dynamic environment. We have areal-time model: actions have a duration. This means that actions of one or more agents can takeplace during overlapping time frames, leading to harmful interference orbeneficial synergy. Agents can perform group actions, which means that themembers of the group perform individual actions in a coordinated manner. In Chapter 5, we develop the programming language GrAPL (Group AgentProgramming Language), intended to program multi-agent systems in which agentscan form temporary alliances to perform group actions. Before a group actions isperformed, the agents communicate with each other to pose demands on details ofthe action and the composition of the group of actors. The programming languagehas a formal operational semantics. We generalise the idea of Chapter 5 in Chapter 6, by looking at group plansinstead of group actions. A group plan is a composed action, consisting of bothindividual actions and group actions, which are partially ordered in time. Weprovide a new high-level coordination language which heterogeneous agents canuse to discuss group plans and to execute them in a synchronised manner

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Rational Agents: Prioritized Goals, Goal Dynamics, and Agent Programming Languages with Declarative Goals

I introduce a specification language for modeling an agent's prioritized goals and their dynamics. I use the situation calculus along with Reiter's solution to the frame problem and predicates for describing agents' knowledge as my base formalism. I further enhance this language by introducing a new sort of infinite paths. Within this language, I discuss how to systematically specify prioritized goals and how to precisely describe the effects of actions on these goals. These actions include adoption and dropping of goals and subgoals. In this framework, an agent's intentions are formally specified as the prioritized intersection of her goals. The ``prioritized'' qualifier above means that the specification must respect the priority ordering of goals when choosing between two incompatible goals. I ensure that the agent's intentions are always consistent with each other and with her knowledge. I investigate two variants with different commitment strategies. Agents specified using the ``optimizing'' agent framework always try to optimize their intentions, while those specified in the ``committed'' agent framework will stick to their intentions even if opportunities to commit to higher priority goals arise when these goals are incompatible with their current intentions. For these, I study properties of prioritized goals and goal change. I also give a definition of subgoals, and prove properties about the goal-subgoal relationship. As an application, I develop a model for a Simple Rational Agent Programming Language (SR-APL) with declarative goals. SR-APL is based on the ``committed agent'' variant of this rich theory, and combines elements from Belief-Desire-Intention (BDI) APLs and the situation calculus based ConGolog APL. Thus SR-APL supports prioritized goals and is grounded on a formal theory of goal change. It ensures that the agent's declarative goals and adopted plans are consistent with each other and with her knowledge. In doing this, I try to bridge the gap between agent theories and practical agent programming languages by providing a model and specification of an idealized BDI agent whose behavior is closer to what a rational agent does. I show that agents programmed in SR-APL satisfy some key rationality requirements