Statistical GGP Game Decomposition

International audienceThis paper presents a statistical approach for the decomposition of games in the General Game Playing framework. General game players can drastically decrease game search cost if they hold a decomposed version of the game. Previous works on decomposition rely on syn-tactical structures, which can be missing from the game description, or on the disjunctive normal form of the rules, which is very costly to compute. We offer an approach to decompose single or multi-player games which can handle the different classes of compound games described in Game Description Language (parallel games, serial games, multiple games). Our method is based on a statistical analysis of relations between actions and fluents. We tested our program on 597 games. Given a timeout of 1 hour and few playouts (1k), our method successfully provides an expert-like decomposition for 521 of them. With a 1 minute timeout and 5k playouts, it provides a decomposition for 434 of them

Towards More Data-Aware Application Integration (extended version)

Although most business application data is stored in relational databases, programming languages and wire formats in integration middleware systems are not table-centric. Due to costly format conversions, data-shipments and faster computation, the trend is to "push-down" the integration operations closer to the storage representation. We address the alternative case of defining declarative, table-centric integration semantics within standard integration systems. For that, we replace the current operator implementations for the well-known Enterprise Integration Patterns by equivalent "in-memory" table processing, and show a practical realization in a conventional integration system for a non-reliable, "data-intensive" messaging example. The results of the runtime analysis show that table-centric processing is promising already in standard, "single-record" message routing and transformations, and can potentially excel the message throughput for "multi-record" table messages.Comment: 18 Pages, extended version of the contribution to British International Conference on Databases (BICOD), 2015, Edinburgh, Scotlan

Synthetizing Qualitative (Logical) Patterns for Pedestrian Simulation from Data

This work introduces a (qualitative) data-driven framework to extract patterns of pedestrian behaviour and synthesize Agent-Based Models. The idea consists in obtaining a rule-based model of pedestrian behaviour by means of automated methods from data mining. In order to extract qualitative rules from data, a mathematical theory called Formal Concept Analysis (FCA) is used. FCA also provides tools for implicational reasoning, which facilitates the design of qualitative simulations from both, observations and other models of pedestrian mobility. The robustness of the method on a general agent-based setting of movable agents within a grid is shown.Ministerio de Economía y Competitividad TIN2013-41086-

Lifted backward search for general game playing

A General Game player is a computer program that can play games of which the rules are only known at run-time. These rules are usually given as a logic program. General Game players commonly apply a tree search over the state space, which is time consuming. In this paper we therefore present a new method that allows a player to detect that a future state satisfies some beneficial properties, without having to explicitly generate that state in the search tree. This may lead to faster algorithms and hence to better performance. Our method employs a search algorithm that searches backwards through formula space rather than state space

A Template-Based Approach Toward Acquisition of Logical Sentences

Ontology-development languages may allow users to supplement frame-based representations with arbitrary logical sentences. In the case of the Ontolingua ontology library, only 10% of the ontologies have any user-defined axioms. We believe the phrase "writing axioms is difficult" accounts for this phenomenon; domain experts often cannot translate their thoughts into symbolic representation. We attempt to reduce this chasm in communication by identifying groups of axioms that manifest common patterns creating `templates' that allow users to compose axioms by `filling-in-the-blanks.' We studied axioms in two public ontology libraries, and derived 20 templates that cover 85% of all the user-defined axioms. We describe our methodology for collecting the templates and present sample templates. We also define several properties of templates that will allow users to find an appropriate template quickly. Thus, our research entails a significant simplification in the process for acquiring axioms from domain experts. We believe that this simplification will foster the introduction of axioms and constraints that are currently missing in the ontologies

Knowledge-Level Analysis of the User Interface Design for a Compositional Modeling System

This paper presents the design of a knowledge acquisition user interface for a compositional modeling system. To facilitate collaborative development of knowledge bases and their reuse, knowledge of the domain is represented in a formal language based on the first-order predicate logic. The vocabulary used is also formally defined explicitly in the same language. However, use of a formal representation language does not make the process of expressing knowledge about the domain easy or efficient for all users. We have designed the knowledge acquisition interface with multiple layers, each intended for a different type of users, such as programmers, knowledge engineers, and domain experts. Though the underlying modeling system employs one representation formalism, the layered interface allows each type of users to interact with the system in terms that are appropriate and efficient for their purposes. This paper is to appear in the proceedings of IFIP Conference on Domain Knowledge for I..