Defining and maintaining agent’s experience in logical agents

DALI is a logic programming agent-oriented language defined in [1,2,3,4], fully formalized in [5,6]. DALI is fully implemented, and has been used in practice in a variety of applications [7,8,9,10]. A stable release of the DALI interpreter is publicly available at [11]. For the definition of DALI we have built under many respects upon our past work about meta-reasoning and reflection in logic programming languages [12,13,14,15,16]. In this work in particular, issues related to meta-level representation of predicates, atoms and rules are discussed in depth.

Lecture Notes in Computer Science, 2004

We acknowledge support by the Information Society Technologies programme of the European Commission, Future and Emerging Technologies under the IST-2001-37004 WASP project.

2006

Abstract. In this paper, we deal with detecting behavioral anomalies in agents. In particular we consider agents defined via logic languages, and we take as a case-study the DALI language previously defined by the authors. We start proposing a formalization of aspects of agent memory and experience and we emphasize how the construction of memories can be a concrete aid for verification of future activities. The anomalies detection process is based on a set of constraints that use the agent past experience to identify behavioral traces ...

2008

Abstract Many interesting architectures for defining intelligent agents have been proposed in the last years. Logic-based architectures have proved effective for reproducing “intelligent” behavior while staying within a rigorous formal setting. In this paper, we present the DALI multi-agent architecture, a logic framework for defining intelligent agents and multiagent systems.

Woa, 2005

In this paper we introduce a form of cooperation among agents based on exchanging sets of rules. In principle, the approach extends to agent societies a feature which is proper of human societies, i.e., the cultural transmission of abilities. However, acquiring knowledge from untrustworthy agents should be avoided, and the new knowledge should be evaluated according to its usefulness. After discussing the general principles of our approach, we present a prototypical implementation. gered as if it were an external one. A DALI agent is able to build a plan in order to reach an objective, by using internal events of a particular kind, called planning goals. Actions are the agent's way of affecting the environment, possibly in reaction to either an external or internal event. An action in DALI can be also a message sent by an agent to another one. Definition 4 (Action): An action is syntactically indicated by postfix A: Action ::= << Atom A >> |message A << Atom, Atom >> Actions take place in the body of rules. If an action has preconditions, they are defined by action rules, emphasized by a new token: Definition 5 (Action rule): An action rule has the form: Action :< P reconditions. Similarly to external and internal events, actions are recorded as past actions. Past events represent the agent's "memory", that makes it capable to perform future activities while having experience of previous events, and of its own previous conclusions. Past events are kept for a certain default amount of time, that can be modified by the user through a suitable directive in the initialization file. A past event is syntactically indicated by the postfix P. Procedurally, DALI is based on an Extended Resolution Procedure that interleaves different activities, and can be tuned by the user via directives. The operational semantics of DALI is based on Dialogue Games Theory [4] [20]: the DALI Interpreter is modeled as a set of cooperating players. By means of this approach one is able to prove formal properies of the language in the form of properties that the game will necessarily fulfil. A. DALI Communication Architecture The DALI communication architecture consists of four levels. The first and last levels implement the DALI/FIPA communication protocol and a filter on communication, i.e. a set of rules that decide whether or not receive (told check level) or send a message (tell check level). The DALI communication filter is specified by means of meta-level rules defining the distinguished predicates tell and told. Whenever a message is received, with content part primitive(Content,Sender) the DALI interpreter automatically looks for a corresponding told rule. If such a rule is found, the interpreter attempts to prove told(Sender, primitive(Content)). If this goal succeeds, then the message is accepted, and primitive(Content)) is added to the set of the external events incoming into the receiver agent. Otherwise, the message is discarded. Symmetrically, the messages that an agent sends are subjected to a check via tell rules. The second level includes a metareasoning layer, that tries to understand message contents, possibly based on ontologies and/or on forms of commonsense reasoning. The third level consists of the DALI interpreter.

Abstract. This paper deals with run-time detection and possible correction of erroneous and/or anomalous behavior in agents defined in datalog-or prologbased logic languages. In particular, we augment our previous approaches by allowing an agent to explicitly observe and record its past behavior so as to be able to decide its best actions, detect anomalous behavior and try to dynamically correct detected problems.

2005

We discuss some features of the new logic programming language DALI for agents and multi-agent systems, also in connection to the issues raised in [12]. We focus in particular on the treatment of proactivity, which is based on the novel mechanism of the internal events and goals. As a case-study, we discuss the design and implementation of an agent capable to perform simple forms of planning. We demonstrate how it is possible in DALI to perform STRIPS-like planning without implementing a meta-interpreter.

Abstract. This paper presents a comprehensive framework for run-time selfchecking of logical agents, by means of temporal axioms to be dynamically checked. These axioms are specified by using an agent-oriented interval temporal logic defined to this purpose. We define syntax, semantics and pragmatics for this new logic, specifically tailored for application to agents. In the resulting framework, we encompass and extend our past work.

Intelligenza Artificiale, 2011

This paper stems from an experience made by Annalisa D'Andrea (with her colleague Daniela Pavone) as a student of the'Artificial Intelligence and Intelligent Agents' graduate course at the University of L'Aquila (held by Prof. Stefania Costantini and Dr. Arianna Tocchio). The experience has been further developed by Annalisa as a Ph. D. student, with her collegue Niva Florio and with the help of Dr. Giovanni De Gasperis.