A Decidable Confluence Test for Cognitive Models in ACT-R

Computational cognitive modeling investigates human cognition by building detailed computational models for cognitive processes. Adaptive Control of Thought - Rational (ACT-R) is a rule-based cognitive architecture that offers a widely employed framework to build such models. There is a sound and complete embedding of ACT-R in Constraint Handling Rules (CHR). Therefore analysis techniques from CHR can be used to reason about computational properties of ACT-R models. For example, confluence is the property that a program yields the same result for the same input regardless of the rules that are applied. In ACT-R models, there are often cognitive processes that should always yield the same result while others e.g. implement strategies to solve a problem that could yield different results. In this paper, a decidable confluence criterion for ACT-R is presented. It allows to identify ACT-R rules that are not confluent. Thereby, the modeler can check if his model has the desired behavior. The sound and complete translation of ACT-R to CHR from prior work is used to come up with a suitable invariant-based confluence criterion from the CHR literature. Proper invariants for translated ACT-R models are identified and proven to be decidable. The presented method coincides with confluence of the original ACT-R models.Comment: To appear in Stefania Costantini, Enrico Franconi, William Van Woensel, Roman Kontchakov, Fariba Sadri, and Dumitru Roman: "Proceedings of RuleML+RR 2017". Springer LNC

Hierarchical planning in BDI agent programming languages: A formal approach

This paper provides a general mechanism and a solid theoretical basis for performing planning within Belief-Desire-Intention (BDI) agents. BDI agent systems have emerged as one of the most widely used approaches to implementing intelligent behaviour in complex dynamic domains, in addition to which they have a strong theoretical background. However, these systems either do not include any built-in capacity for "lookahead" type of planning or they do it only at the implementation level without any precise defined semantics. In some situations, the ability to plan ahead is clearly desirable or even mandatory for ensuring success. Also, a precise definition of how planning can be integrated into a BDI system is highly desirable. By building on the underlying similarities between BDI systems and Hierarchical Task Network (HTN) planners, we present a formal semantics for a BDI agent programming language which cleanly incorporates HTN-style planning as a built-in feature. We argue that the resulting integrated agent programming language combines the advantages of both BDI agent systems and hierarchical offline planners

A BDI agent programming language with failure handling, declarative goals, and planning

Agents are an important technology that have the potential to take over contemporary methods for analysing, designing, and implementing complex software. The Belief- Desire-Intention (BDI) agent paradigm has proven to be one of the major approaches to intelligent agent systems, both in academia and in industry. Typical BDI agent-oriented programming languages rely on user-provided ''plan libraries'' to achieve goals, and online context sensitive subgoal selection and expansion. These allow for the development of systems that are extremely flexible and responsive to the environment, and as a result, well suited for complex applications with (soft) real-time reasoning and control requirements. Nonetheless, complex decision making that goes beyond, but is compatible with, run-time context-dependent plan selection is one of the most natural and important next steps within this technology. In this paper we develop a typical BDI-style agent-oriented programming language that enhances usual BDI programming style with three distinguished features: declarative goals, look-ahead planning, and failure handling. First, an account that mixes both procedural and declarative aspects of goals is necessary in order to reason about important properties of goals and to decouple plans from what these plans are meant to achieve. Second, lookahead deliberation about the effects of one choice of expansion over another is clearly desirable or even mandatory in many circumstances so as to guarantee goal achievability and to avoid undesired situations. Finally, a failure handling mechanism, suitably integrated with both declarative goals and planning, is required in order to model an adequate level of commitment to goals, as well as to be consistent with most real BDI implemented systems

Business process model customisation using domain-driven controlled variability management and rule generation

Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

Business process model customisation using domain-driven controlled variability management and rule generation

Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

handling, declarative goals, and planning

A BDI agent programming language with failur

Multi-agent planning using an abductive : event calculus

Temporal reasoning within distributed Artificial Intelligence Systems is faced with the problem of concurrent streams of action. Well known, logic-based systems using the SITUATION CALCULUS solve the frame problem in a purely linear manner. Recent research, however, has revealed that the EVENT CALCULUS under the abduction principle is capable of nonlinear planning. In this report, we present a planning service module which incorporates this approach into a constraint logic framework and even allows a notion of strong nonlinearity. The work includes the axiomatisation of appropriate versions of the EVENT CALCULUS, the development of a suitably sound and complete proof procedure that supports abduction and the implementation of both of these layers on the constraint platform OZ. We demonstrate prototypically how this module, EVE, can be integrated into an existing multi-agent architecture and evaluate the behaviour of such agents within an application domain, the loading dock scenario

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface