There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Multiagent systems are made up of multiple interacting intelligent agents -- computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice It is suitable for classroom use or independent study This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999 Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty The chapters and the overall book are designed to be self-contained and understandable without additional material Supplemental resources are available on the book's Web site Contributors:Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jurgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein

Multiagent Systems

Temporal logic comes in two varieties: linear-time temporal logic assumes implicit universal quantification over all paths that are generated by the execution of a system; branching-time temporal logic allows explicit existential and universal quantification over all paths. We introduce a third, more general variety of temporal logic: alternating-time temporal logic offers selective quantification over those paths that are possible outcomes of games, such as the game in which the system and the environment alternate moves. While linear-time and branching-time logics are natural specification languages for closed systems, alternating-time logics are natural specification languages for open systems. For example, by preceding the temporal operator "eventually" with a selective path quantifier, we can specify that in the game between the system and the environment, the system has a strategy to reach a certain state. The problems of receptiveness, realizability, and controllability can be formulated as model-checking problems for alternating-time formulas. Depending on whether or not we admit arbitrary nesting of selective path quantifiers and temporal operators, we obtain the two alternating-time temporal logics ATL and ATLa.ATL and ATLa are interpreted over concurrent game structures. Every state transition of a concurrent game structure results from a choice of moves, one for each player. The players represent individual components and the environment of an open system. Concurrent game structures can capture various forms of synchronous composition for open systems, and if augmented with fairness constraints, also asynchronous composition. Over structures without fairness constraints, the model-checking complexity of ATL is linear in the size of the game structure and length of the formula, and the symbolic model-checking algorithm for CTL extends with few modifications to ATL. Over structures with weak-fairness constraints, ATL model checking requires the solution of 1-pair Rabin games, and can be done in polynomial time. Over structures with strong-fairness constraints, ATL model checking requires the solution of games with Boolean combinations of Buchi conditions, and can be done in PSPACE. In the case of ATLa, the model-checking problem is closely related to the synthesis problem for linear-time formulas, and requires doubly exponential time.

/pdf/alternating-time-temporal-logic-3du0km9tzh.pdf

Alternating-time temporal logic

Conventional type systems specify interfaces in terms of values and domains. We present a light-weight formalism that captures the temporal aspects of software component interfaces. Specifically, we use an automata-based language to capture both input assumptions about the order in which the methods of a component are called, and output guarantees about the order in which the component calls external methods. The formalism supports automatic compatability checks between interface models, and thus constitutes a type system for component interaction. Unlike traditional uses of automata, our formalism is based on an optimistic approach to composition, and on an alternating approach to design refinement. According to the optimistic approach, two components are compatible if there is some environment that can make them work together. According to the alternating approach, one interface refines another if it has weaker input assumptions, and stronger output guarantees. We show that these notions have game-theoretic foundations that lead to efficient algorithms for checking compatibility and refinement.

Interface automata

Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically. The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field.This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily

Handbook of Knowledge Representation

R. Alur1, T.A. Henzinger2, F.Y.C. Mang2, S. Qadeer2, S.K. Rajamani2, and S. Tasiran2 1 Computer & Information Science Department, University of Pennsylvania, Philadelphia, PA 19104. Computing Science Research Center, Bell Laboratories, Murray Hill, NJ 07974. alur@cis.upenn.edu 2 Electrical Engineering & Computer Sciences Department, University of California, Berkeley, CA 94720. ftah,fmang,shaz,sriramr,serdarg@eecs.berkeley.edu

/pdf/mocha-modularity-in-model-checking-12jhj0hl31.pdf

MOCHA: Modularity in Model Checking

We present a formal methodology and tool for uncovering errors in the interaction of software modules. Our methodology consists of a suite of languages for defining software interfaces, and algorithms for checking interface compatibility. We focus on interfaces that explain the method-call dependencies between software modules. Such an interface makes assumptions about the environment in the form of call and availability constraints. A call constraint restricts the accessibility of local methods to certain external methods. An availability constraint restricts the accessibility of local methods to certain states of the module. For example, the interface for a file server with local methods open and read may assert that a file cannot be read without having been opened. Checking interface compatibility requires the solution of games, and in the presence of availability constraints, of pushdown games. Based on this methodology, we have implemented a tool that has uncovered incompatibilities in TinyOS, a small operating system for sensor nodes in adhoc networks.

/pdf/interface-compatibility-checking-for-software-modules-1y79cfiain.pdf

Interface Compatibility Checking for Software Modules

Model checking is a practical tool for automated debugging of embedded software. In model checking, a high-level description of a system is compared against a logical correctness requirement to discover inconsistencies. Since model checking is based on exhaustive state-space exploration and the size of the state space of a design grows exponentially with the size of the description, scalability remains a challenge. We have thus developed techniques for exploiting modular design structure during model checking, and the model checker jMocha (Java MOdel-CHecking Algorithm) is based on this theme. Instead of manipulating unstructured state-transition graphs, it supports the hierarchical modeling framework of reactive modules. jMocha is a growing interactive software environment for specification, simulation and verification, and is intended as a vehicle for the development of new verification algorithms and approaches. It is written in Java and uses native C-code BDD libraries from VIS. jMocha offers: (1) a GUI that looks familiar to Windows/Java users; (2) a simulator that displays traces in a message sequence chart fashion; (3) requirements verification both by symbolic and enumerative model checking; (4) implementation verification by checking trace containment; (5) a proof manager that aids compositional and assume-guarantee reasoning; and (6) SLANG (Scripting LANGuage) for the rapid and structured development of new verification algorithms. jMocha is available publicly at ; it is a successor and extension of the original Mocha tool that was entirely written in C.

/pdf/jmocha-a-model-checking-tool-that-exploits-design-structure-apugraww8n.pdf

JMOCHA: a model checking tool that exploits design structure

We present interface models that describe both the input assumptions of a component, and its output behavior. By enabling us to check that the input assumptions of a component are met in a design, interface models provide a compatibility check for component-based design. When refining a design into an implementation, interface models require that the output behavior of a component satisfies the design specification only when the input assumptions of the specification are satisfied, yielding greater flexibility in the choice of implementations. Technically, our interface models are games between two players, Input and Output; the duality of the players accounts for the dual roles of inputs and outputs in composition and refinement. We present two interface models in detail, one for a simple synchronous form of interaction between components typical in hardware, and the other for more complex synchronous interactions on bidirectional connections. As an example, we specify the interface of a bidirectional bus, with the input assumption that at any time at most one component has write access to the bus. For these interface models, we present algorithms for compatibility and refinement checking, and we describe efficient symbolic implementations.

/pdf/synchronous-and-bidirectional-component-interfaces-terg0llomv.pdf

Freddy Y. C. Mang

Papers

MOCHA: Modularity in Model Checking

Interface Compatibility Checking for Software Modules

JMOCHA: a model checking tool that exploits design structure

Synchronous and Bidirectional Component Interfaces

Synchronous and bidirectional component interfaces