We describe how to embed a simple typed functional logic programming language in Haskell. The embedding is a natural extension of the Prolog embedding by Seres and Spivey [16]. To get full static typing we need to use the Haskell extensions of quantified types and the ST-monad. 1 Introduction Over the last ten to twenty years, there have been many attempts to combine the flavours of logic and functional programming [3]. Among these, the most well-known ones are the programming languages Curry [4], Escher [13], and Mercury [14]. Curry and Escher can be seen as variations on Haskell, where logic programming features are added. Mercury can be seen as an improvement of Prolog, where types and functional programming features are added. All three are completely new and autonomous languages. Defining a new programming language has as a drawback for the developer to build a new compiler, and for the user to learn a new language. A different approach which has gained a lot of popularity ...

Abstract. Inductive logic programming is a form of machine learning from examples which employs the representation formalism of clausal logic. One of the earliest inductive logic programming systems was Ehud Shapiro’s Model Inference System [90], which could synthesise simple recursive programs like append/3. Many of the techniques devised by Shapiro, such as top-down search of program clauses by refinement operators, the use of intensional background knowledge, and the capability of inducing recursive clauses, are still in use today. On the other hand, significant advances have been made regarding dealing with noisy data, efficient heuristic and stochastic search methods, the use of logical representations going beyond definite clauses, and restricting the search space by means of declarative bias. The latter is a general term denoting any form of restrictions on the syntactic form of possible hypotheses. These include the use of types, input/output mode declarations, and clause schemata. Recently, some researchers have started using alternatives to Prolog featuring strong typing and real functions, which alleviate the need for some of the above ad-hoc mechanisms. Others have gone beyond Prolog by investigating learning tasks in which the hypotheses are not definite clause programs, but for instance sets of indefinite clauses or denials, constraint logic programs, or clauses representing association rules. The chapter gives an accessible introduction to the above topics. In addition, it outlines the main current research directions which have been strongly influenced by recent developments in data mining and challenging real-life applications. 1

Go! is a multi-paradigm programming language that is oriented to the needs of programming secure, production quality, agent based applications. It is multi-threaded, strongly typed and higher order (in the functional programming sense). It has relation, function and action procedure definitions. Threads execute action procedures, calling functions and querying relations as need be. Threads in different agents communicate and coordinate using asynchronous messages. Threads within the same agent can also use shared dynamic relations acting as Linda-style tuple stores. In this paper we introduce the essential features of Go!. We then illustrate them by programming a simple multi-agent application comprising hybrid reactive/deliberative agents interacting in a simulated ballroom. The dancer agents negotiate to enter into joint commitments to dance a particular dance (e.g. polka) they both desire. When the dance is announced, they dance together. The agents ’ reactive and deliberative components are concurrently executing threads which communicate and coordinate using belief, desire and intention memory stores. We believe such a multi-threaded agent architecture represents a powerful and natural style of agent implementation, for which Go! is well suited. 1