ALPprolog --- A New Logic Programming Method for Dynamic Domains

Logic programming is a powerful paradigm for programming autonomous agents in dynamic domains, as witnessed by languages such as Golog and Flux. In this work we present ALPprolog, an expressive, yet efficient, logic programming language for the online control of agents that have to reason about incomplete information and sensing actions.Comment: 16 page

Action Logic Programs: How to Specify Strategic Behavior in Dynamic Domains Using Logical Rules

We discuss a new concept of agent programs that combines logic programming with reasoning about actions. These agent logic programs are characterized by a clear separation between the specification of the agent’s strategic behavior and the underlying theory about the agent’s actions and their effects. This makes it a generic, declarative agent programming language, which can be combined with an action representation formalism of one’s choice. We present a declarative semantics for agent logic programs along with (two versions of) a sound and complete operational semantics, which combines the standard inference mechanisms for (constraint) logic programs with reasoning about actions

Under consideration for publication in Theory and Practice of Logic Programming ALPprolog -A New Logic Programming Method for Dynamic Domains

Abstract Logic programming is a powerful paradigm for programming autonomous agents in dynamic domains, as witnessed by languages such as Golog and Flux. In this work we present ALPprolog, an expressive, yet efficient, logic programming language for the online control of agents that have to reason about incomplete information and sensing actions

Putting ABox Updates into Action

When trying to apply recently developed approaches for updating Description Logic ABoxes in the context of an action programming language, one encounters two problems. First, updates generate so-called Boolean ABoxes, which cannot be handled by traditional Description Logic reasoners. Second, iterated update operations result in very large Boolean ABoxes, which, however, contain a huge amount of redundant information. In this paper, we address both issues from a practical point of view

Introducing LoCo, a Logic for Configuration Problems

In this paper we present the core of LoCo, a logic-based high-level representation language for expressing configuration problems. LoCo shall allow to model these problems in an intuitive and declarative way, the dynamic aspects of configuration notwithstanding. Our logic enforces that configurations contain only finitely many components and reasoning can be reduced to the task of model construction.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

aspcud: A Linux Package Configuration Tool Based on Answer Set Programming

We present the Linux package configuration tool aspcud based on Answer Set Programming. In particular, we detail aspcud's preprocessor turning a CUDF specification into a set of logical facts.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

(Re)configuration based on model generation

Reconfiguration is an important activity for companies selling configurable products or services which have a long life time. However, identification of a set of required changes in a legacy configuration is a hard problem, since even small changes in the requirements might imply significant modifications. In this paper we show a solution based on answer set programming, which is a logic-based knowledge representation formalism well suited for a compact description of (re)configuration problems. Its applicability is demonstrated on simple abstractions of several real-world scenarios. The evaluation of our solution on a set of benchmark instances derived from commercial (re)configuration problems shows its practical applicability.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation

Bacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor

The Partner Units Problem − A Constraint Programming Case Study

The Partner Units Problem is a challenging combinatorial search problem that originates in the domain of security and surveillance. Technically it consists of partitioning a bipartite graph under side conditions. In this work we describe how constraint programming technology can be leveraged to tackle the problem. We address problem modelling, symmetry breaking and problem-specific search strategies. We introduce the best search strategy known to date as well as a powerful new implied constraint for pruning the search space. Finally, we present implementations in ECLiPSe Prolog and the MINION constraint solver and compare these to a state-of-the-art dedicated algorithm