Agent Programming in 3APL

An intriguing and relatively new metaphor in the programming community is that of an intelligent agent. The idea is to view programs as intelligent agents acting on our behalf. By using the metaphor of intelligent agents the programmer views programs as entities which have a mental state consisting of beliefs and goals. The computational behaviour of an agent is explained in terms of the decisions the agent makes on the basis of its mental state. It is assumed that this way of looking at programs may enhance the design and development of complex computational systems.To support this new style of programming, we propose the agent programming language 3APL. 3APL has a clear and formally defined semantics. The operational semantics of the language is defined by means of transition systems. 3APL is a combination of imperative and logic programming. From imperative programming the language inherits the full range of regular programming constructs, including recursive procedures, and a notion of state-based computation. States of agents, however, are belief or knowledge bases, which are different from the usual variable assignments of imperative programming. From logic programming, the language inherits the proof as computation model as a basic means of computation for querying the belief base of an agent. These features are well-understood and provide a solid basis for a structured agent programming language. Moreover, on top of that 3APL agents use so-called practical reasoning rules which extend the familiar recursive rules of imperative programming in several ways. Practical reasoning rules can be used to monitor and revise the goals of an agent, and provide an agent with reflective capabilities.Applying the metaphor of intelligent agents means taking a design stance. From this perspective, a program is taken as an entity with a mental state, which acts pro-actively and reactively, and has reflective capabilities. We illustrate how the metaphor of intelligent agents is supported by the programming language. We also discuss the design of control structures for rule-based agent languages. A control structure provides a solution to the problem of which goals and which rules an agent should select. We provide a concrete and intuitive ordering on the practical reasoning rules on which such a selection mechanism can be based. The ordering is based on the metaphor of intelligent agents. Furthermore, we provide a language with a formal semantics for programming control structures. The main idea is not to integrate this language into the agent language itself, but to provide the facilities for programming control structures at a meta level. The operational semantics is accordingly specified at the meta level, by means of a meta transition system.     

Reasoning about agent deliberation

We present a family of sound and complete logics for reasoning about deliberation strategies for SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementation of cognitive agents with beliefs, goals and plans. The logics are variants of PDL, and allow us to prove safety and liveness properties of SimpleAPL agent programs under different deliberation strategies. We show how to axiomatise different deliberation strategies for SimpleAPL programs, and, for each strategy we prove a correspondence between the operational semantics of SimpleAPL and the models of the corresponding logic. We illustrate the utility of our approach with an example in which we show how to verify correctness properties for a simple agent program under different deliberation strategies.     

A framework for linguistic logic programming

Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real‐world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD‐style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc.     

Toward a programming theory for rational agents

An important problem in agent verification is a lack of proper understanding of the relation between agent programs on the one hand and agent logics on the other. Understanding this relation would help to establish that an agent programming language is both conceptually well-founded and well-behaved, as well as yield a way to reason about agent programs by means of agent logics. As a step toward bridging this gap, we study several issues that need to be resolved in order to establish a precise mathematical relation between a modal agent logic and an agent programming language specified by means of an operational semantics. In this paper, we present an agent programming theory that provides both an agent programming language as well as a corresponding agent verification logic to verify agent programs. The theory is developed in stages to show, first, how a modal semantics can be grounded in a state-based semantics, and, second, how denotational semantics can be used to define the mathematical relation connecting the logic and agent programming language. Additionally, it is shown how to integrate declarative goals and add precompiled plans to the programming theory. In particular, we discuss the use of the concept of higher-order goals in our theory. Other issues such as a complete axiomatization and the complexity of decision procedures for the verification logic are not the focus of this paper and remain for future investigation. Part of this research was carried out while the first author was affiliated with the Nijmegen Institute for Cognition and Information, Radboud University Nijmegen.     

Agents with emotions

This paper discusses the role of emotions in artificial agent design and implementation. The syntax and semantics of a simplified version of a logic‐based agent‐oriented programming language is presented. This programming language facilitates the implementation of artificial agents with emotions. Four types of emotions are distinguished: happiness, sadness, anger, and fear. These emotions are defined relative to agent's goals and plans. The emotions result from the agent's deliberation process and influence the deliberation process. The semantics of each emotion type is incorporated in the transition semantics of the presented agent‐oriented programming language. © 2010 Wiley Periodicals, Inc.     

Active logic semantics for a single agent in a static world

For some time we have been developing, and have had significant practical success with, a time-sensitive, contradiction-tolerant logical reasoning engine called the active logic machine (ALMA). The current paper details a semantics for a general version of the underlying logical formalism, active logic. Central to active logic are special rules controlling the inheritance of beliefs in general (and of beliefs about the current time in particular), very tight controls on what can be derived from direct contradictions ($P\mathrm{\&}\neg P$), and mechanisms allowing an agent to represent and reason about its own beliefs and past reasoning. Furthermore, inspired by the notion that until an agent notices that a set of beliefs is contradictory, that set seems consistent (and the agent therefore reasons with it as if it were consistent), we introduce an “apperception function” that represents an agent's limited awareness of its own beliefs, and serves to modify inconsistent belief sets so as to yield consistent sets. Using these ideas, we introduce a new definition of logical consequence in the context of active logic, as well as a new definition of soundness such that, when reasoning with consistent premises, all classically sound rules remain sound in our new sense. However, not everything that is classically sound remains sound in our sense, for by classical definitions, all rules with contradictory premises are vacuously sound, whereas in active logic not everything follows from a contradiction.     

HYPOTHETICAL REASONING ABOUT ACTIONS: FROM SITUATION CALCULUS TO EVENT CALCULUS

Hypothetical reasoning about actions is the activity of preevaluating the effect of performing actions in a changing domain; this reasoning underlies applications of knowledge representation, such as planning and explanation generation. Action effects are often specified in the language of situation calculus, introduced by McCarthy and Hayes in 1969. More recently, the event calculus has been defined to describe actual actions, i.e., those that have occurred in the past, and their effects on the domain. Altough the two formalisms share the basic ontology of atomic actions and fluents, situation calculus cannot represent actual actions while event calculus cannot represent hypotethical actions. In this article, the language and the axioms of event calculus are extended to allow representing and reasoning about hypothetical actions, performed either at the present time or in the past, altough counterfactuals are not supported. Both event calculus and its extension are defined as logic programs so that theories are readily adaptable for Prolog query interpretation. For a reasonably large class of theories and queries, Prolog interpretation is shown to be sound and complete w.r.t. the main semantics for logic programs.     

The expressiveness of spider diagrams augmented with constants

Spider diagrams are a visual language for expressing logical statements or constraints. Several sound and complete spider diagram systems have been developed and it has been shown that they are equivalent in expressive power to monadic first order logic with equality. However, these sound and complete spider diagram systems do not contain syntactic elements analogous to constants in first order predicate logic. We extend the spider diagram language to include constant spiders which represent specific individuals. Formal semantics are given for the extended diagram language. We prove that this extended system is equivalent in expressive power to the language of spider diagrams without constants and, hence, equivalent to monadic first order logic with equality.     

Applying restriction constraints to deductive databases

An operation for restricting deductive databases represented as logic programs is introduced. The constraints are coded in a separate database, and the operator puts the two databases together in order to provide a restricted view of the original database. The operator is given a semantics in terms of the immediate consequence operator. Then a transformational implementation is given and its correctness is proved with respect to the abstract semantics. The approach is presented at first for positive programs and it is then extended to take negation as failure into account.     

Database query languages and functional logic programming

Functional logic programming is a paradigm which integrates functional and logic programming. It is based on the use of rewriting rules for defining programs, and rewriting for goal solving. In this context, goals, usually, consist of equality (and, sometimes, inequality) constraints, which are solved in order to obtain answers, represented by means of substitutions. On the other hand, database programming languages involve a data model, a data definition language and, finally, a query language against the data defined according to the data model. To use functional logic programming as a database programming language, (1) we will propose a data model involving the main features adopted from functional logic programming (for instance, handling of partial and infinite data), (2) we will use conditional rewriting rules as data definition language, and finally, (3) we will deal with equality and inequality constraints as query language. Moreover, as most database systems, (4) we will propose an extended relational calculus and algebra, which can be used as alternative query languages in this framework. Finally, (5) we will prove that three alternative query languages are equivalent.     

On the relationship between annotated logic programs and nonmonotonic formalisms

Abstract

In the past we developed a semantics for a restricted annotated logic language for inheritance reasoning. Here we generalize it to annotated Horn logic programs. We first provide a formal account of the language, describe its semantics, and provide an interpreter written in Prolog for it. We then investigate its relationship to Belnap's 4-valued logic, Gelfond and Lifschitz's semantics for logic programs with negation, Brewka's prioritized default logics and other annotated logics due to Kifer et al.     

FLUX中负析取约束的研究与实现*

FLUX是基于流演算的逻辑程序语言,实现agents在不完全状态下对其动作和感知信息进行逻辑推理。FLUX利用不同的约束来编码不完全状态,但现有的约束并不能覆盖所有流演算状态公式,这势必影响FLUX的应用范围。针对以上问题,在FLUX中引入负析取约束,利用约束处理规则集（CHRs）加以实现,并基于流演算基础语义分析了负析取约束的正确性,从而提高了FLUX对不完全状态的表达能力。     

Providing effective decision support: Modeling users and their requirements

The major premise of this paper is that in order for a DSS to be effective in a given problem domain, it is important to model the decision-making behavior of the user over and above traditional problem solving concerns. This is achieved by extending the traditional planning framework based on first-order logic to include modal logic. This extended framework is then used to represent beliefs and desires of the user, communicative actions performed by the user and the system, as well as the usual goals, task-related actions etc. The essence of this approach, then, is to view natural language utterances of the user of a DSS as speech acts which can be modeled using the extended framework; this view can, in turn, be used to interpret natural language utterances of the user.     

N-Prolog and equivalence of logic programs

The aim of this work is to develop a declarative semantics for N-Prolog with negation as failure. N-Prolog is an extension of Prolog proposed by Gabbay and Reyle (1984, 1985), which allows for occurrences of nested implications in both goals and clauses. Our starting point is an operational semantics of the language defined by means of top-down derivation trees. Negation as finite failure can be naturally introduced in this context. A goal-G may be inferred from a database if every top-down derivation of G from the database finitely fails, i.e., contains a failure node at finite height.Our purpose is to give a logical interpretation of the underlying operational semantics. In the present work (Part 1) we take into consideration only the basic problems of determining such an interpretation, so that our analysis will concentrate on the propositional case. Nevertheless we give an intuitive account of how to extend our results to a first order language. A full treatment of N-Prolog with quantifiers will be deferred to the second part of this work.Our main contribution to the logical understanding of N-Prolog is the development of a notion of modal completion for programs, or databases. N-Prolog deductions turn out to be sound and complete with respect to such completions. More exactly, we introduce a natural modal three-valued logic PK and we prove that a goal is derivable from a propositional program if and only if it is implied by the completion of the program in the logic PK. This result holds for arbitrary programs. We assume no syntactic restriction, such as stratification (Apt et al. 1988; Bonner and McCarty 1990). In particular, we allow for arbitrary recursion through negation.Our semantical analysis heavily relies on a notion of intensional equivalence for programs and goals. This notion is naturally induced by the operational semantics, and is preserved under substitution of equivalent subexpressions. Basing on this substitution property we develop a theory of normal forms of programs and goals. Every program can be effectively transformed into an equivalent program in normal form. From the simple and uniform structure of programs in normal form one may directly define the completion.     

Active Integrity Constraints for Database Consistency Maintenance

This paper introduces active integrity constraints (AICs), an extension of integrity constraints for consistent database maintenance. An active integrity constraint is a special constraint whose body contains a conjunction of literals which must be false and whose head contains a disjunction of update actions representing actions (insertions and deletions of tuples) to be performed if the constraint is not satisfied (that is its body is true). The AICs work in a domino-like manner as the satisfaction of one AIC may trigger the violation and therefore the activation of another one. The paper also introduces founded repairs, which are minimal sets of update actions that make the database consistent, and are specified and “supported” by active integrity constraints. The paper presents: 1) a formal declarative semantics allowing the computation of founded repairs and 2) a characterization of this semantics obtained by rewriting active integrity constraints into disjunctive logic rules, so that founded repairs can be derived from the answer sets of the derived logic program. Finally, the paper studies the computational complexity of computing founded repairs.     

Autoepistemic logics as a unifying framework for the semantics of logic programs

In this paper, it is shown that a three-valued autoepistemic logic provides an elegant unifying framework for some of the major semantics of normal and disjunctive logic programs and logic programs with classical negation, namely, the stable semantics, the well-founded semantics, supported models, Fitting's semantics, Kunen's semantics, the stationary semantics, and answer sets. For the first time, so many semantics are embedded into one logic. The framework extends previous results—by Gelfond, Lifschitz, Marek, Subrahmanian, and Truszczynski —on the relationships between logic programming and Moore's autoepistemic logic. The framework suggests several new semantics for negation-as-failure. In particular, we will introduce the epistemic semantics for disjunctive logic programs. In order to motivate the epistemic semantics, an interesting class of applications called ignorance tests will be formalized; it will be proved that ignorance tests can be defined by means of the epistemic semantics, but not by means of the old semantics for disjunctive programs. The autoepistemic framework provides a formal foundation for an environment that integrates different forms of negation. The role of classical negation and various forms of negation-by-failure in logic programming will be briefly discussed.     

事务逻辑对象库语言

对象封装了结构和行为.对象数据库为大规模复杂应用提供良好的建模方法和实现手段.对象与逻辑结合导致目前对演绎对象库的研究.然而,这些研究基本上针对对象的结构描述,而很少涉及到对象的动态行为的描述.该文重点研究对象的动态行为,分析对象特征：继承和重载对事务语义的影响,并设计了一个事务对象库语言TOL(transaction object base language).首先分析TOL中的基本更新活动的特征,然后研究其事务的模型论语义.TOL模型论语义基于通路结构.