Function in Device Representation

We explore the meanings of the terms ‘structure’, ‘behaviour’, and, especially, ‘function’ in engineering practice. Computers provide great assistance in calculation tasks in engineering practice, but they also have great potential for helping with reasoning tasks. However, realising this vision requires precision in representing engineering knowledge, in which the terms mentioned above play a central role. We start with a simple ontology for representing objects and causal interactions between objects. Using this ontology, we investigate a range of meanings for the terms of interest. Specifically, we distinguish between function as effect on the environment, and a device-centred view of device function. In the former view, function is seen as an intended or desired role that an artifact plays in its environment. We identify an important concept called mode of deployment that is often left implicit, but whose explicit representation is necessary for correct and complete reasoning. We discuss the task of design and design verification in this framework. We end with a discussion that relates needs in the world to functions of artifacts created to satisfy the needs.     

Compact preference representation and Boolean games

Game theory is a widely used formal model for studying strategical interactions between agents. Boolean games (Harrenstein, Logic in conflict, PhD thesis, 2004; Harrenstein et al., Theoretical Aspects of Rationality and Knowledge, pp. 287–298, San Francisco Morgan Kaufmann, 2001) yield a compact representation of 2-player zero-sum static games with binary preferences: an agent’s strategy consists of a truth assignment of the propositional variables she controls, and a player’s preferences are expressed by a plain propositional formula. These restrictions (2-player, zero-sum, binary preferences) strongly limit the expressivity of the framework. We first generalize the framework to n-player games which are not necessarily zero-sum. We give simple characterizations of Nash equilibria and dominated strategies, and investigate the computational complexity of the associated problems. Then, we relax the last restriction by coupling Boolean games with a representation, namely, CP-nets. This article is a revised and extended version of the two conference articles [4] and [3].     

Merged processes: a new condensed representation of Petri net behaviour

Model checking based on Petri net unfoldings is an approach widely applied to cope with the state space explosion problem. In this paper, we propose a new condensed representation of a Petri net’s behaviour called merged processes, which copes well not only with concurrency, but also with other sources of state space explosion, viz sequences of choices and non-safeness. Moreover, this representation is sufficiently similar to the traditional unfoldings, so that a large body of results developed for the latter can be re-used. Experimental results indicate that the proposed representation of a Petri net’s behaviour alleviates the state space explosion problem to a significant degree and is suitable for model checking.V. Khomenko is a Royal Academy of Engineering/Epsrc Research Fellow supported by the RAEng/Epsrc grant EP/C53400X/1 (Davac).M. Koutny is supported by the EC IST grant 511599 (Rodin).W. Vogler is supported by the DFG-project STG-Dekomposition VO 615/7-1     

Region–based theory of discrete spaces: A proximity approach

We introduce Boolean proximity algebras as a generalization of Efremovič proximities which are suitable in reasoning about discrete regions. Following Stone’s representation theorem for Boolean algebras, it is shown that each such algebra is isomorphic to a substructure of a complete and atomic Boolean proximity algebra. Co-operation was supported by EC COST Action 274 “Theory and Applications of Relational Structures as Knowledge Instruments” (TARSKI), , and NATO Collaborative Linkage Grant PST.CLG 977641.     

Towards an environment interface standard for agent platforms

We introduce an interface for connecting agent platforms to environments. This interface provides generic functionality for executing actions and for perceiving changes in an agent’s environment. It also provides support for managing an environment, e.g., for starting, pausing and terminating it. Among the benefits of such an interface are (1) standard functionality is provided by the interface implementation itself, and (2) agent platforms that support the interface can connect to any environment that implements the interface. This significantly reduces effort required from agent and environment programmers as the environment code needed to implement the interface needs to be written only once. We propose that the interface presented may be used as a standard that enables agents to control entities in environments. Our starting point for designing such a generic interface is based on a careful study of the various interfaces used by different agent programming languages to connect agent programs to environments. We discuss several case studies that use our interface (an elevator simulator, the well-known agent contest, and an implementation of the interface to connect agents to bots in Unreal Tournament 2004).     

The Interplay Between the Speaker’s and the Hearer’s Perspective

The neutralization of contrasts in form or meaning that is sometimes observed in language production and comprehension is at odds with the classical view that language is a systematic one-to-one pairing of forms and meanings. This special issue is concerned with patterns of forms and meanings in language. The papers in this special issue arose from a series of workshops that were organized to explore variants of bidirectional Optimality Theory and Game Theory as models of the interplay between the speaker’s and the hearer’s perspective.     

Random Bichromatic Matchings

Given a graph with edges colored Red and Blue, we study the problem of sampling and approximately counting the number of matchings with exactly k Red edges. We solve the problem of estimating the number of perfect matchings with exactly k Red edges for dense graphs. We study a Markov chain on the space of all matchings of a graph that favors matchings with k Red edges. We show that it is rapidly mixing using non-traditional canonical paths that can backtrack. We show that this chain can be used to sample matchings in the 2-dimensional toroidal lattice of any fixed size ℓ with k Red edges, where the horizontal edges are Red and the vertical edges are Blue. An extended abstract appeared in J.R. Correa, A. Hevia and M.A. Kiwi (eds.) Proceedings of the 7th Latin American Theoretical Informatics Symposium, LNCS 3887, pp. 190–201, Springer, 2006. N. Bhatnagar’s and D. Randall’s research was supported in part by NSF grants CCR-0515105 and DMS-0505505. V.V. Vazirani’s research was supported in part by NSF grants 0311541, 0220343 and CCR-0515186. N. Bhatnagar’s and E. Vigoda’s research was supported in part by NSF grant CCR-0455666.     

CAESAR_SOLVE: A generic library for on-the-fly resolution of alternation-free Boolean equation systems

Boolean equation systems (Bess) provide a useful framework for modeling various verification problems on finite-state concurrent systems, such as equivalence checking and model checking. These problems can be solved on the fly (i.e., without constructing explicitly the state space of the system under analysis) by using a demand-driven construction and resolution of the corresponding Bes. In this article, we present a generic software library dedicated to on-the-fly resolution of alternation-free Bess. Four resolution algorithms are currently provided by the library: algorithms A1 and A2 are general, the latter being optimized to produce small-depth diagnostics, whereas algorithms A3 and A4 are specialized for handling acyclic and disjunctive/conjunctive Bess in a memory-efficient way. The library has been developed within the Cadp verification toolbox using the generic Open/Caesar environment and is currently used for three purposes: on-the-fly equivalence checking modulo five widely used equivalence relations, on-the-fly model checking of regular alternation-free modal μ-calculus, and on-the-fly reduction of state spaces based on τ-confluence .     

People, Information Systems and Change

Information systems are the glue between people and computers. Both the social and business environments are in a continual, some might say chaotic, state of change while computer hardware continues to double its performance about every 18 months. This presents a major challenge for information system developers.  The term user-friendly is an old one, but one which has come to take on a multitude of meanings. However, in today’s context we might well take a user-friendly system to be one where the technology fits the user’s cognitive models of the activity in hand. This article looks at the relationship between information systems and the changing demands of their users as the underlying theme for the current issue of Cognition, Technology and Work.  People, both as individuals and organisations, change. The functionalist viewpoint, which attempts to freeze and inhibit such change, has failed systems developers on numerous occasions. Responding to, and building on, change in the social environment is still a significant research issue for information systems specialists who need to be able to create living information systems.     

Runtime and Programming Support for Memory Adaptation in Scientific Applications via Local Disk and Remote Memory

The ever increasing memory demands of many scientific applications and the complexity of today’s shared computational resources still require the occasional use of virtual memory, network memory, or even out-of-core implementations, with well known drawbacks in performance and usability. In Mills et al. (Adapting to memory pressure from within scientific applications on multiprogrammed COWS. In: International Parallel and Distributed Processing Symposium, IPDPS, Santa Fe, NM, 2004), we introduced a basic framework for a runtime, user-level library, MMlib, in which DRAM is treated as a dynamic size cache for large memory objects residing on local disk. Application developers can specify and access these objects through MMlib, enabling their application to execute optimally under variable memory availability, using as much DRAM as fluctuating memory levels will allow. In this paper, we first extend our earlier MMlib prototype from a proof of concept to a usable, robust, and flexible library. We present a general framework that enables fully customizable memory malleability in a wide variety of scientific applications. We provide several necessary enhancements to the environment sensing capabilities of MMlib, and introduce a remote memory capability, based on MPI communication of cached memory blocks between ‘compute nodes’ and designated memory servers. The increasing speed of interconnection networks makes a remote memory approach attractive, especially at the large granularity present in large scientific applications. We show experimental results from three important scientific applications that require the general MMlib framework. The memory-adaptive versions perform nearly optimally under constant memory pressure and execute harmoniously with other applications competing for memory, without thrashing the memory system. Under constant memory pressure, we observe execution time improvements of factors between three and five over relying solely on the virtual memory system. With remote memory employed, these factors are even larger and significantly better than other, system-level remote memory implementations.     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

Emergence of Collective Behavior in Evolving Populations of Flying Agents

We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively un-constrained system in which the behavior of agents is governed by evolved computer programs. The first system demonstrates the evolution of a form of multicellular organization, while the second demonstrates the evolution of a form of altruistic food sharing. In this article we describe both systems in detail, document the emergence of collective behavior, and argue that these systems present new opportunities for the study of group dynamics in an evolutionary context. We also provide a brief overview of the breve simulation environment in which the systems were produced, and of breve’s facilities for the rapid, exploratory development of visualization strategies for artificial life.     

Building intelligent collaborative interface agents with the ICAGENT development framework

This paper describes the implementation of intelligent collaborative interface agents using the intelligent collaborative agent (ICagent) development framework. In particular, the paper presents the implementation of a collaborative interface agent that acts as a tutor in the context of an educational software application. The agent deliberates socially with users following the SharedPlans model of collaborative activity. Social deliberation requires interface agents to make their desires and intentions clear to the application users, being in constant communication with them, to understand the context of their activity and to reconcile their own and users’ desires in the overall context of action. Reconciliation of users’ desires allows agents to recognize the situations where users need help. The paper briefly presents the ICagent development framework, describes the implementation of the interface agent, and discusses an example of the behavior of the agent during a collaboration session.     

Genomic control of agent morphogenesis in a physically correct virtual environment

Based on the analysis of the morphogenesis process of real biological organisms, the basic principles are formulated for the simulation of genomic control of the morphogenesis of a virtual agent in a physically correct environment. A model of the genome of a compound agent’s body composed of different functional subsystems is developed. A timing algorithm for genetically conditioned processes of regeneration and division of agent’s microcells is developed. The problem of forming agents with a morphology that is locally optimal for a given environment is formulated as a multi-generation optimization problem in a genetic algorithm. The fitness function is defined as the life duration of agents. Constraints are connected with the physical correctness of an environment and an energy deficit in the environment. Agent genomes are considered as chromosomes in the genetic algorithm. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 42–54, March–April 2008.     

Mining probabilistic automata: a statistical view of sequential pattern mining

During the past decade, sequential pattern mining has been the core of numerous research efforts. It is now possible to efficiently extract knowledge of users’ behavior from a huge set of sequences collected over time. This has applications in various domains such as purchases in supermarkets, Web site visits, etc. However, sequence mining algorithms do little to control the risks of extracting false discoveries or overlooking true knowledge. In this paper, the theoretical conditions to achieve a relevant sequence mining process are examined. Then, the article offers a statistical view of sequence mining which has the following advantages: First, it uses a compact and generalized representation of the original sequences in the form of a probabilistic automaton. Second, it integrates statistical constraints to guarantee the extraction of significant patterns. Finally, it provides an interesting solution in a privacy preserving context in order to respect individuals’ information. An application in car flow modeling is presented, showing the ability of our algorithm (acsm) to discover frequent routes without any private information. Comparisons with a classical sequence mining algorithm (spam) are made, showing the effectiveness of our approach.     

Mental states as multi-context systems

Although Belief-Desire-Intention (BDI) agents have been deeply investigated from both a theoretical and a pragmatic perspective, less attention has been paid to the inherent recursive structure of mental states, which plays an essential role when modelling high level interaction between intelligent agents. This paper tries to capture this property by introducing a multi-context approach to the representation of mental states. A semantics for multi-context formalisms is provided based on the definition of “mental structure”, which is a hierarchical lattice of triangular modules <x,B,D>, where the component x represents the agent x’s mental state as a whole, while B and D represent specifically x’s beliefs and x’s desires. If other mental attitudes, as intention and commitment, are to be considers as primitives, then they can be embodied in the basic module, otherwise they can be represented in terms of beliefs and desires. The old notion of clause is rediscovered in order to facilitate the heavy automated theorem-proving necessary to exploit the potentiality of the formalism for the intelligent interaction with the external environment. The main advantages of this approach are the support for “unconsciousness” and the fact that inferences themselves can be modelled as mental attitudes. Some advanced dynamics of mental states, as the abductive revision of mental states after the reception of a communication, will easily be applied over this formalism.      

A formal model of emotions for an empathic rational dialog agent

Recent research has shown that virtual agents expressing empathic emotions toward users have the potential to enhance human–machine interaction. To provide empathic capabilities to a rational dialog agent, we propose a formal model of emotions based on an empirical and theoretical analysis of the users’ conditions of emotion elicitation. The emotions are represented by particular mental states of the agent, composed of beliefs, uncertainties and intentions. This semantically grounded formal representation enables a rational dialog agent to identify from a dialogical situation the empathic emotion that it should express. An implementation and an evaluation of an empathic rational dialog agent have enabled us to validate the proposed model of empathy.     

Minimum Weakly Fundamental Cycle Bases Are Hard To Find

In the last years, new variants of the minimum cycle basis (MCB) problem and new classes of cycle bases have been introduced, as motivated by several applications from disparate areas of scientific and technological inquiry. At present, the complexity status of the MCB problem is settled only for undirected, directed, and strictly fundamental cycle bases (SFCB’s). Weakly fundamental cycle bases (WFCB’s) form a natural superclass of SFCB’s. A cycle basis of a graph G is a WFCB iff ν=0 or there exists an edge e of G and a circuit C _i in such that is a WFCB of G∖e. WFCB’s still possess several of the nice properties offered by SFCB’s. At the same time, several classes of graphs enjoying WFCB’s of cost asymptotically inferior to the cost of the cheapest SFCB’s have been found and exhibited in the literature. Considered also the computational difficulty of finding cheap SFCB’s, these works advocated an in-depth study of WFCB’s. In this paper, we settle the complexity status of the MCB problem for WFCB’s (the MWFCB problem). The problem turns out to be -hard. However, in this paper, we also offer a simple and practical 2⌈log ₂ n⌉-approximation algorithm for the MWFCB problem. In O(n ν) time, this algorithm actually returns a WFCB whose cost is at most 2⌈log ₂ n⌉∑ _e∈E(G) w _e , thus allowing a fast 2⌈log ₂ n⌉-approximation also for the MCB problem. With this algorithm, we provide tight bounds on the cost of any MCB and MWFCB.     

Databases with uncertainty and lineage

This paper introduces uldbs, an extension of relational databases with simple yet expressive constructs for representing and manipulating both lineage and uncertainty. Uncertain data and data lineage are two important areas of data management that have been considered extensively in isolation, however many applications require the features in tandem. Fundamentally, lineage enables simple and consistent representation of uncertain data, it correlates uncertainty in query results with uncertainty in the input data, and query processing with lineage and uncertainty together presents computational benefits over treating them separately. We show that the uldb representation is complete, and that it permits straightforward implementation of many relational operations. We define two notions of uldb minimality—data-minimal and lineage-minimal—and study minimization of uldb representations under both notions. With lineage, derived relations are no longer self-contained: their uncertainty depends on uncertainty in the base data. We provide an algorithm for the new operation of extracting a database subset in the presence of interconnected uncertainty. We also show how uldbs enable a new approach to query processing in probabilistic databases. Finally, we describe the current state of the Trio system, our implementation of uldbs under development at Stanford. This work was supported by the National Science Foundation under grants IIS-0324431, IIS-1098447, and IIS-9985114, by DARPA Contract #03-000225, and by a grant from the Boeing Corporation.     

A logic-based agent that plans for extended reachability goals

Planning to reach a goal is an essential capability for rational agents. In general, a goal specifies a condition to be achieved at the end of the plan execution. In this article, we introduce nondeterministic planning for extended reachability goals (i.e., goals that also specify a condition to be preserved during the plan execution). We show that, when this kind of goal is considered, the temporal logic ctl turns out to be inadequate to formalize plan synthesis and plan validation algorithms. This is mainly due to the fact that the ctl’s semantics cannot discern among the various actions that produce state transitions. To overcome this limitation, we propose a new temporal logic called α-ctl. Then, based on this new logic, we implement a planner capable of synthesizing reliable plans for extended reachability goals, as a side effect of model checking.