Marina De Vos

Answer set programming for representing and reasoning about virtual institutions

It is recognised that institutions are potentially powerful means for making agent interactions effective and efficient, but institutions will only really be useful when, as in other safety-critical scenarios, it is possible to prove that particular properties do or do not hold for all possible encounters. In contrast to symbolic model-checking, answer set programming permits the statement of problems and queries in domain-specific terms as executable logic programs, thus eliminating the gap between specification and verification language. Furthermore, results are presented in the same terms. In this paper we describe the use of answer set programs as an institutional modelling technique. We demonstrate that our institutional model can be intuitively be mapped into an answer set program such that the ordered event traces of the former can be obtained as the answer sets of the latter, allowing for an easy way to query properties of models.

Choice Logic Programs and Nash Equilibria in Strategic Games

We define choice logic programs as negation-free datalog programs that allow rules to have exclusive-only disjunctions in the head. We show that choice programs are equivalent to semi-negative datalog programs, at least as far as stable models are concerned. We also discuss an application where strategic games can be naturally formulated as choice programs; it turns out that the stable models of such programs capture exactly the set of Nash equilibria.

Specifying and analysing agent-based social institutions using answer set programming

In this paper we discuss the use of the Answer Set Programming paradigm for representing and analysing specifications of agent-based institutions. We outline the features of institutions we model, and describe how they are translated into ASP programs which can then be used to verify properties of the specifications. We demonstrate the effectiveness of this approach through the institutions of property and exchange.

TOAST: applying answer set programming to superoptimisation

Answer set programming (ASP) is a form of declarative programming particularly suited to difficult combinatorial search problems. However, it has yet to be used for more than a handful of large-scale applications, which are needed to demonstrate the strengths of ASP and to motivate the development of tools and methodology. This paper describes such a large-scale application, the TOAST (Total Optimisation using Answer Set Technology) system, which seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine to handle searching over complex, non-regular search spaces, with the experimental results suggesting that this is a viable approach to the optimisation problem and demonstrates the scalability of a variety of solvers.

Energy efficient zone based routing protocol for MANETs

Mobile Ad Hoc Networks (MANET) are self-configuring infrastructureless networks of mobile devices connected via wireless links. Each device can send and receive data, but it should also forward traffic unrelated to its own use. All need to maintain their autonomy, and effectively preserve their resources (e.g. battery power). Moreover, they can leave the network at any time. Their intrinsic dynamicity and fault tolerance makes them suitable for applications, such as emergency response and disaster relief, when infrastructure is nonexistent or damaged due to natural disasters, such as earthquakes and flooding, as well as more mundane, day-to-day, uses where their flexibility would be advantageous.Routing is the fundamental research issue for such networks and refers to finding and maintaining routes between nodes. Moreover, it involves selecting the best route where many may be available. However, due to the freedom of movement of nodes, new routes need to be constantly recalculated. Most routing protocols use pure broadcasting to discover new routes, which takes up a substantial amount of bandwidth. Intelligent rebroadcasting reduces these overheads by calculating the usefulness of a rebroadcast, and the likelihood of message collisions. Unfortunately, this introduces latency and parts of the network may become unreachable. This paper discusses the Zone based Routing with Parallel Collision Guided Broadcasting Protocol (ZCG) that uses parallel and distributed broadcasting technique (Basurra et al., 2010) 8 to reduce redundant broadcasting and to accelerate the path discovery process, while maintaining a high reachability ratio as well as keeping node energy consumption low.ZCG uses a one hop clustering algorithm that splits the network into zones led by reliable leaders that are mostly static and have plentiful battery resources. The performance characteristics of the ZCG protocol are established through simulations by comparing it to other well-known routing protocols, namely the: AODV and DSR. It emerges that ZCG performs well under many circumstances.

Automatic music composition using answer set programming

Music composition used to be a pen and paper activity. These days music is often composed with the aid of computer software, even to the point where the computer composes parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named Anton, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes Anton unique in the growing area of algorithmic composition. With near real-time composition, Anton reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an ???off-the-shelf??? reasoning engine, Anton provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems.

Normative design using inductive learning

In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules and revise the existing ones. The learning mechanism is guided by the designer who describes the desired properties of the framework through use cases, comprising (i) event traces that capture possible scenarios, and (ii) a state that describes the desired outcome. The learning process then proposes additional rules, or changes to current rules, to satisfy the constraints expressed in the use cases. Thus, the contribution of this paper is a process for the elaboration and revision of a normative framework by means of a semi-automatic and iterative process driven from specifications of (un)desirable behaviour. The process integrates a novel and general methodology for theory revision based on ASP.

LAIMA: a multi-agent platform using ordered choice logic programming

Multi-agent systems (MAS) can take many forms depending on the characteristics of the agents populating them. Amongst the more demanding properties with respect to the design and implementation of multi-agent system is how these agents may individually reason and communicate about their knowledge and beliefs, with a view to cooperation and collaboration. In this paper, we present a deductive reasoning multi-agent platform using an extension of answer set programming (ASP). We show that it is capable of dealing with the specification and implementation of the systems architecture, communication and the individual agents reasoning capacities. Agents are represented as Ordered Choice Logic Programs (OCLP) as a way of modelling their knowledge and reasoning capacities, with communication between the agents regulated by uni-directional channels transporting information based on their answer sets. In the implementation of our system we combine the extensibility of the JADE framework with the flexibility of the OCT front-end to the Smodels answer set solver. The power of this approach is demonstrated by a multi-agent system reasoning about equilibria of extensive games with perfect information.

ASPVIZ: Declarative Visualisation and Animation Using Answer Set Programming

Answer set programming provides a powerful platform for model-based reasoning problems. The answer sets are solutions, but for many non-trivial problems post-processing is often necessary for human readability. In this paper we describe a method and a tool for visualising answer sets in which we exploit answer set programming itself to define how visualisations are constructed. An exciting potential application of our method is to assist in the debugging of answer set programs that, as a consequence of their declarative nature, are not amenable to traditional approaches: visual rendering of answer sets offers a way to help programmers spot false and missing solutions.

A model-based approach to the automatic revision of secondary legislation

Conflicts between laws can readily arise in situations governed by different laws, a case in point being when the context of an inferior law (or set of regulations) is altered through revision of a superior law. Being able to detect these conflicts automatically and resolve them, for example by proposing revisions to one of the modelled laws or policies, would be highly beneficial for legislators, legal departments of organizations or anybody having to incorporate legal requirements into their own procedures. In this paper we present a model based approach for detecting and finding legal conflicts through a combination of a formal model of legal specifications and a computational model based on answer set programming and inductive logic programming. Given specific scenarios (descriptions of courses of action), our model-based approach can automatically detect whether these scenarios could lead to contradictory outcomes in the different legal specifications. Using these conflicts as use cases, we apply inductive logic programming (ILP) to learn revisions to the legal component that is the source of the conflict. We illustrate our approach using a case-study where a university has to change its studentship programme after the government brings in new immigration regulations.