Formal language

About: Formal language is a research topic. Over the lifetime, 5763 publications have been published within this topic receiving 154114 citations.

Framer: Planning Models from Natural Language Action Descriptions

Abstract: In this paper, we describe an approach for learning planning domain models directly from natural language (NL) descriptions of activity sequences. The modelling problem has been identified as a bottleneck for the widespread exploitation of various technologies in Artificial Intelligence, including automated planners. There have been great advances in modelling assisting and model generation tools, including a wide range of domain model acquisition tools. However, for modelling tools, there is the underlying assumption that the user can formulate the problem using some formal language. And even in the case of the domain model acquisition tools, there is still a requirement to specify input plans in an easily machine readable format. Providing this type of input is impractical for many potential users. This motivates us to generate planning domain models directly from NL descriptions, as this would provide an important step in extending the widespread adoption of planning techniques. We start from NL descriptions of actions and use NL analysis to construct structured representations, from which we construct formal representations of the action sequences. The generated action sequences provide the necessary structured input for inducing a PDDL domain, using domain model acquisition technology. In order to capture a concise planning model, we use an estimate of functional similarity, so sentences that describe similar behaviours are represented by the same planning operator. We validate our approach with a user study, where participants are tasked with describing the activities occurring in several videos. Then our system is used to learn planning domain models using the participants' NL input. We demonstrate that our approach is effective at learning models on these tasks.

Some transformational extensions of montague grammar

Abstract: Richard Montague’s work on English, as represented in Montague (1970a), (1970b), (1972), represents the first systematic attempt to apply the logician’s methods of formal syntax and semantics to natural language. With few exceptions,1 linguists and logicians had previously been agreed, although for different reasons, that the apparatus developed by logicians for treating the syntax and semantics of artificially constructed formal languages, while obviously fruitful within its restricted domain, was not in any direct way applicable to the analysis of natural languages. Logicians seem to have felt that natural languages were too unsystematic, too full of vagueness and ambiguity, to be amenable to their rigorous methods, or if susceptible to formal treatment, only at great cost.2 Linguists, on the other hand, emphasize their own concern for psychological reality, and the logicians’ lack of it, in eschewing the logicians’ approach: linguists, at least those of the Chomskyan school, are searching for a characterization of the class of possible human languages, hoping to gain thereby some insight into the structure of the mind, and the formal languages constructed by logicians appear to depart radically from the structures common to actual natural languages.

Petri nets and szilard languages

Abstract: We investigate the properties of firing sequences (f.s.) of Petri nets and relate' them to other well-known families of formal languages. We prove in particular that the complement of the f.s. set is context free, and consequently neither the class of f.s. sets (according to some definition) nor Szilard languages are closed with respect to the complement. After introducing new normal forms for Petri nets, we prove that the reachability problem is equivalent to the emptiness problem for the intersection of Szilard languages. 1. INTRODUCTION The focus of this paper is on the formal properties of Petri nets, but the methodology presented should also apply to related models for representing parallel processes such as those by Karp and Miller (1969) and Gostelow

The Logic of Action

Abstract: In this article we provide a brief overview of the logic of action in philosophy, linguistics, computer science and artificial intelligence. The logic of action is the formal study of action in which formal languages are the main tool of analysis. The concept of action is of central interest to many disciplines: the social sciences including economics, the humanities including history and literature, psychology, linguistics, law, computer science, artificial intelligence, and probably others. In philosophy it has been studied since the beginning because of its importance for epistemology and, particularly, ethics; and since a few decades it is even studied for its own sake. But it is in the logic of action that action is studied in the most abstract way. The logic of action began in philosophy. But it has also played a certain role in linguistics. And currently it is of great importance in computer science and artificial intelligence. For our purposes it is natural to separate the accounts of these developments. 1 The logic of action in philosophy 1.1 Historical overview Already St Anselm studied the concept of action in a way that must be classified as logical; had he known symbolic logic, he would certainly have made use of it. (Cf. [33] and [101].) In modern times the subject was introduced by, among others, Alan Ross Anderson, Frederick B. Fitch, Stig Kanger, and Georg Henrik von Wright; Kanger’s work was further developed by his students Ingmar Porn and Lars Lindahl. The first clearly semantic account was given by Brian F. Chellas in [11]. (For a more detailed account, see [83] or the mini-history in [8].) Today there are two rather different groups of theories that may be described as falling under the term logic of action. One, the result of the creation of Nuel Belnap and his many collaborators, may be called stit theory (a term that will be explained in the next paragraph). The other is dynamic logic. Both are connected