Multi-shot ASP solving with clingo (1705.09811v2)

Abstract: We introduce a new flexible paradigm of grounding and solving in Answer Set Programming (ASP), which we refer to as multi-shot ASP solving, and present its implementation in the ASP system clingo. Multi-shot ASP solving features grounding and solving processes that deal with continuously changing logic programs. In doing so, they remain operative and accommodate changes in a seamless way. For instance, such processes allow for advanced forms of search, as in optimization or theory solving, or interaction with an environment, as in robotics or query-answering. Common to them is that the problem specification evolves during the reasoning process, either because data or constraints are added, deleted, or replaced. This evolutionary aspect adds another dimension to ASP since it brings about state changing operations. We address this issue by providing an operational semantics that characterizes grounding and solving processes in multi-shot ASP solving. This characterization provides a semantic account of grounder and solver states along with the operations manipulating them. The operative nature of multi-shot solving avoids redundancies in relaunching grounder and solver programs and benefits from the solver's learning capacities. clingo accomplishes this by complementing ASP's declarative input language with control capacities. On the declarative side, a new directive allows for structuring logic programs into named and parameterizable subprograms. The grounding and integration of these subprograms into the solving process is completely modular and fully controllable from the procedural side. To this end, clingo offers a new application programming interface that is conveniently accessible via scripting languages.

• The paper introduces a novel multi-shot ASP solving approach that incrementally evolves logic programs without a complete restart.
• It utilizes parameterizable subprograms and dynamic grounding to integrate external inputs for adaptive problem solving.
• Case studies in robotics and real-time analysis demonstrate its practical benefits and potential for advanced AI applications.

Multi-shot ASP Solving with Clingo

The paper introduces a novel paradigm for grounding and solving in Answer Set Programming (ASP), which is termed multi-shot ASP solving, and details its implementation in the ASP system Clingo. This paradigm significantly extends traditional ASP capabilities by allowing for the incremental and dynamic evolution of logic programs within a single ASP solving process. The multi-shot approach facilitates advanced forms of problem-solving, particularly in domains involving optimization, interaction with changing environments, and iterative query processing, by continuously accommodating modifications to the logic program under consideration.

Multi-shot ASP solving in Clingo is achieved by maintaining logic program states that can evolve as the problem changes. It supports state-changing operations such as adding, removing, and modifying logic program components without requiring a complete restart of the solving process. This operational flexibility is underpinned by a robust operational semantics framework that defines the states of the grounder and solver and the operations that manipulate them.

One of the standout features of multi-shot ASP solving is its ability to interact dynamically with external environments, which is especially useful in areas like robotics and real-time data analysis. These interactions are facilitated through Clingo's application programming interface (API), which allows for the integration of external events and inputs that can influence the logic program during execution.

Key technical innovations include the use of parameterizable subprograms, grounding context management, and seamless integration of external atoms. These give users fine-grained control over the problem-solving process, allowing subprograms to be selectively grounded and solved based on evolving requirements.

The implications of multi-shot ASP solving are profound in both theoretical and practical domains. Theoretically, it necessitates a reevaluation of traditional ASP semantics and encourages the development of new models that can account for dynamic and evolving problem spaces. Practically, it empowers developers to create more adaptable and responsive ASP applications that can handle continuous input changes without significant performance overhead.

The authors illustrate the practical benefits of multi-shot solving with multiple case studies, including incremental solving strategies akin to those previously offered by systems like iclingo and oclingo. They also explore the application of multi-shot solving to the $n$-Queens problem, highlighting its capacity to manage evolving constraint systems.

The research suggests several potential future developments, particularly in the field of artificial intelligence, where adaptive and context-aware problem-solving is increasingly critical. Multi-shot ASP solving with Clingo represents a significant advancement towards more interactive and intelligent ASP-based systems, offering a flexible and powerful tool for tackling complex, real-world problems.

This paper is a substantial contribution to the field of logic programming, opening new avenues for research and application by providing a versatile and efficient solving paradigm that aligns well with the dynamic nature of modern AI challenges.