Martin Brain

Debugging ASP programs by means of ASP

Answer-set programming (ASP) has become an important paradigm for declarative problem solving in recent years. However, to further improve the usability of answer-set programs, the development of software-engineering tools is vital. In particular, the area of debugging provides a challenge in both theoretical and practical terms. This is due to the purely declarative nature of ASP that, on the one hand, calls for solver-independent methodologies and, on the other hand, does not directly apply to tracing techniques. In this paper, we propose a novel methodology, which rests within ASP itself, to sort out errors on the conceptual level. Our method makes use of tagging, where the program to be analyzed is rewritten using dedicated control atoms. This provides a flexible way to specify different types of debugging requests and a first step towards a dedicated (meta level) debugging language.

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.

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.

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.

An Automatable Formal Semantics for IEEE-754 Floating-Point Arithmetic

Automated reasoning tools often provide little or no support to reason accurately and efficiently about floating-point arithmetic. As a consequence, software verification systems that use these tools are unable to reason reliably about programs containing floating-point calculations or may give unsound results. These deficiencies are in stark contrast to the increasing awareness that the improper use of floating-point arithmetic in programs can lead to unintuitive and harmful defects in software. To promote coordinated efforts towards building efficient and accurate floating-point reasoning engines, this paper presents a formalization of the IEEE-754 standard for floating-point arithmetic as a theory in many-sorted first-order logic. Benefits include a standardized syntax and unambiguous semantics, allowing tool interoperability and sharing of benchmarks, and providing a basis for automated, formal analysis of programs that process floating-point data.

Interpolation-Based Verification of Floating-Point Programs with Abstract CDCL

One approach for smt solvers to improve efficiency is to delegate reasoning to abstract domains. Solvers using abstract domains do not support interpolation and cannot be used for interpolation-based verification. We extend Abstract Conflict Driven Clause Learning (acdcl) solvers with proof generation and interpolation. Our results lead to the first interpolation procedure for floating-point logic and subsequently, the first interpolation-based verifiers for programs with floating-point variables. We demonstrate the potential of this approach by verifying a number of programs which are challenging for current verification tools.

A new-generation automated warehousing capability

A novel and highly adaptable concept is presented whereby automated warehouses can be built based on a series of simple modules with their inherent feature of scalability and reconfigurability. A potential application example of such a warehousing system is modelled to indicate the level of capability that the concept can provide. Physical infrastructure and operational control events within the system are illustrated in the paper. Simulation results demonstrate that this type of automated warehousing system can simultaneously deliver large numbers of items from storage modules to assigned collection locations with minimal delay. The concept is readily applicable within the wider logistics sector. The system performance can be enhanced by deploying an integrated warehouse control and management mechanism using automatic identification and data capture techniques and wireless communication networks. A framework on application of these emerging technologies in order to achieve the desired coordinated functionality of automated warehouse operations is proposed in the paper.

An Abstract Interpretation of DPLLT

dpllt is a central algorithm for Satisfiability Modulo Theories smt solvers. The algorithm combines results of reasoning about the Boolean structure of a formula with reasoning about conjunctions of theory facts to decide satisfiability. This architecture enables modern solvers to combine the performance benefits of propositional satisfiability solvers and conjunctive theory solvers. We characterise dpllt as an abstract interpretation algorithm that computes a product of two abstractions. Our characterisation allows a new understanding of dpllt as an instance of an abstract procedure to combine reasoning engines beyond propositional solvers and conjunctive theory solvers. In addition, we show theoretically that the split into Boolean and theory reasoning is sometimes unnecessary and demonstrate empirically that it can be detrimental to performance.

ANTON: Composing Logic and Logic Composing

In most styles of music, composition is governed by a set of rules. We demonstrate that approaching the automation and analysis of composition declaratively, by expressing these rules in a suitable logical language, powerful and expressive intelligent composition tools can easily be built. This paper describes the use of answer set programming to construct an automated system, named Anton , that can compose both melodic and harmonic music, diagnose errors in human compositions and serve as a computer-aided composition tool.