The max-sum labeling problem, defined as maximizing a sum of binary (ie, pairwise)
functions of discrete variables, is a general NP-hard optimization problem with many …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

We describe a new selection technique for evolutionary multiobjective optimization
algorithms in which the unit of selection is a hyperbox in objective space. In this technique …

Writing the second edition of this text was a wonderful opportunity for a more mature
presentation than I was able to give 13 years ago. The intent still is to give a self-contained …

Stochastic algorithms are among the best methods for solving computationally hard search
and reasoning problems. The run time of such procedures can vary significantly from …

Artificial Intelligence (AI) is useful. AI can deliver more functionality for reduced cost. AI
should be used more widely but won't be unless developers can trust adaptive …

We study the runtime distributions of backtrack procedures for propositional satisfiability and
constraint satisfaction. Such procedures often exhibit a large variability in performance. Our …

In this paper, we show that the models of random CSP instances proposed by Xu and Li [K.
Xu, W. Li, Exact phase transitions in random constraint satisfaction problems, Journal of …

In this paper we propose a new type of random CSP model, called Model RB, which is a
revision to the standard Model B. It is proved that phase transitions from a region where …

One of the field in which models of abstraction have been proposed is Artificial Intelligence
(AI). This chapter has two parts: one presents an overview of the formal models, either …