The effect of practice on the operative form of a rule was investigated by giving subjects an easy, perfectly predictive classification rule, followed by training in applying that rule to a set of practice items. On a subsequent transfer test, the accuracy and speed of classifying new items was strongly affected by similarity to previously seen items, suggesting that the effect of practice was ...

We propose an interpretable rule-based classification system based on ideas from Boolean compressed sensing. We represent the problem of learning individual conjunctive clauses or individual disjunctive clauses as a Boolean group testing problem, and apply a novel linear programming relaxation to find solutions. We derive results for exact rule recovery which parallel the conditions for exact r...

The relaxed planning heuristic is a prominent state-to-goal estimator function for domain-independent forward-chaining heuristic search and local search planning. It enriches the state-space traversal of almost all currently available suboptimal state-of-the-art planning systems. While current domain description languages allow general arithmetic expressions in precondition and effect lists, th...

Less Flexibility First(LFF) principle is inspired and developed by enhancing some rule-of-thumb guidelines resulting from the generation-long work experience of human professionals in ancient days. In this paper, we generalize this principle to the classical Traveling Salesman Problem and propose a tour construction heuristic. Our new heuristic is closely related to Cheapest Insertion, a well-k...

We study an approach to learning heuristics for planning domains from example solutions. There has been little work on learning heuristics for the types of domains used in deterministic and stochastic planning competitions. Perhaps one reason for this is the challenge of providing a compact heuristic language that facilitates learning. Here we introduce a new representation for heuristics based...

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving ta...

In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm’s performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003)...

Separate-and-conquer type rule inductionalgorithms suchasRipper, solve aK>2classproblembyconverting it into a sequence of K − 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in the order of increasing prior probabilities. Although the heuristic works well in practice, there is much room for improvement. In this paper, we propose a novel approach to improve thi...