AGENT-BASED NEGOTIATION PLATFORM IN COLLABORATIVE NETWORKED ENVIRONMENT

This paper proposes an agent-based platform to model and support parallel and concurrent negotiations among organizations acting in the same industrial market. The underlying complexity is to model the dynamic environment where multi-attribute and multi-participant negotiations are racing over a set of heterogeneous resources. The metaphor Interaction Abstract Machines (IAMs) is used to model the parallelism and the non-deterministic aspects of the negotiation processes that occur in Collaborative Networked Environment

ON THE BASIC BINDING STRUCTURE OF A BASIC INTERACTION SCHEME

ABSTRACT This paper introduces and analyses the idea of the binding structure of a social interaction scheme. Binding structures are proposed as means to model the binding power that an interaction scheme imposes on agents interacting according to the scheme, in a social context. The paper considers the case of a basic interaction scheme, namely, the basic Producer-Consumer scheme, to explain the way the binding structure builds on the operational structure of that scheme, in particular how the binding structure is constructed in terms of binding relations. In addition, the non-reducibility of binding structures to their component binding relations is established. The importance of a detailed analysis of the derivation scheme of binding structures from operational structures of interaction schemes, including the role that legal and moral norms may play in such derivation, is briefly indicated. The relevance of the ideas introduced in the paper for the concrete representation of macro-level social structures as macro-level artifacts in social simulation is also indicated

Resilience, reliability, and coordination in autonomous multi-agent systems

Acknowledgements The research reported in this paper was funded and supported by various grants over the years: Robotics and AI in Nuclear (RAIN) Hub (EP/R026084/1); Future AI and Robotics for Space (FAIR-SPACE) Hub (EP/R026092/1); Offshore Robotics for Certification of Assets (ORCA) Hub (EP/R026173/1); the Royal Academy of Engineering under the Chair in Emerging Technologies scheme; Trustworthy Autonomous Systems “Verifiability Node” (EP/V026801); Scrutable Autonomous Systems (EP/J012084/1); Supporting Security Policy with Effective Digital Intervention (EP/P011829/1); The International Technology Alliance in Network and Information Sciences.Peer reviewedPostprin

Model Checking Logics of Social Commitments for Agent Communication

This thesis is about specifying and verifying communications among autonomous and possibly heterogeneous agents, which are the key principle for constructing effective open multi-agent systems (MASs). Effective systems are those that successfully achieve applicability, feasibility, error-freeness and balance between expressiveness and verification efficiency aspects. Over the last two decades, the MAS community has advocated social commitments, which successfully provide a powerful representation for modeling communications in the figure of business contracts from one agent to another. While modeling communications using commitments provides a fundamental basis for capturing flexible communications and helps address the challenge of ensuring compliance with specifications, the designers and business process modelers of the system as a whole cannot guarantee that an agent complies with its commitments as supposed to or at least not wantonly violate or cancel them. They may still wish to first formulate the notion of commitment-based protocols that regulate communications among agents and then establish formal verification (e.g., model checking) by which compliance verification in those protocols is possible. In this thesis, we address the aforementioned challenges by firstly developing a new branching-time temporal logic---called ACTL*c---that extends CTL* with modal operators for representing and reasoning about commitments and all associated actions. The proposed semantics for ACL (agent communication language) messages in terms of commitments and their actions is formal, declarative, meaningful, verifiable and semi-computationally grounded. We use ACTL*c to derive a new specification language of commitment-based protocols, which is expressive and suitable for model checking. We introduce a reduction method to formally transform the problem of model checking ACTL*c to the problem of model checking GCTL* so that the use of the CWB-NC model checker is possible. We prove the soundness of our reduction method and implement it on top of CWB-NC. To check the effectiveness of our reduction method, we report the verification results of the NetBill protocol and Contract Net protocol against some properties. In addition to the reduction method, we develop a new symbolic algorithm to perform model checking ACTL*c. To balance between expressiveness and verification efficiency, we secondly adopt a refined fragment of ACTL*c, called CTLC, an extension of CTL with modalities for commitments and their fulfillment. We extend the formalism of interpreted systems introduced to develop MASs with shared and unshared variables and considered agents' local states in the definition of a full-computationally grounded semantics for ACL messages using commitments. We present reasonable axioms of commitment and fulfillment modalities. In our verification technique, the problem of model checking CTLC is reduced into the problems of model checking ARCTL and GCTL* so that respectively extended NuSMV and CWB-NC (as a benchmark) are usable. We prove the soundness of our reduction methods and then implement them on top of the extended NuSMV and CWB-NC model checkers. To evaluate the effectiveness of our reduction methods, we verified the correctness of two business case studies. We finally proceed to develop a new symbolic model checking algorithm to directly verify commitments and their fulfillment and commitment-based protocols. We analyze the time complexity of CTLC model checking for explicit models and its space complexity for concurrent programs that provide compact representations. We prove that although CTLC extends CTL, their model checking algorithms still have the same time complexity for explicit models, and the same space complexity for concurrent programs. We fully implement the proposed algorithm on top of MCMAS, a model checker for the verification of MASs, and then check its efficiency and scalability using an industrial case study

The development of Spatial Intelligent Agents With Geographic Information Systems

The manipulation of geographic information (GI) has been considered, by most of its users, as a very complex process and has involved the development of specific applications called geographic information systems (GIS). A new subdiscipline of Information Science called Geographic Information Science (GISc) has been proposed by the GIS research community on the grounds that there are specific characteristics not only to GI but also to the processes involved in its manipulation. The thesis draws on several research issues which are part of the agenda in GISc: The complexity of handling spatial/geographic information, spatial reasoning in dynamical systems, integration of several types of application, human-computer interaction and spatio-temporal issues. In this context, this dissertation proposes the application of a new computational paradigm, intelligent agents in GISc. Intelligent agents are “computational systems that inhabit some complex dynamic environment, sense and act autonomously, and by doing so realise a set of goals or tasks for which they are designed “ (Maes, 1995). The aim of this dissertation is to analyse the potential of research in intelligent agents in GISc and to explore the use of simple learning techniques to improve the adaptability of spatial intelligent agents. The thesis involves the following objectives: to analyse the needs of research in GISc in the areas of reasoning about geographic space; to study the potential of intelligent agents in that area of research; to explore the use of simple learning techniques to improve the adaptability of intelligent agents for geographic information; and to explore the implementation environments of GIS software for the integration of intelligent agent systems. The primary contributions of this research are three case studies which use intelligent agents in a spatial or geographic context: a simple non-adaptive interface assistant for the printing and plotting tool of Smallworld GIS; an intelligent assistant that uses memory-based reasoning to identify and locate specific-purpose geographic information; a simulation of a car park where agents are cars that use reinforcement learning techniques to improve their parking performance