We review the use of factor graphs for the modeling and solving of large-scale inference
problems in robotics. Factor graphs are a family of probabilistic graphical models, other …

/ '" '" / Page 1 JUDEA PEARL GRAPHICAL MODELS FOR PROBABILISTIC AND CAUSAL
REASONING 1 INTRODUCTION This chapter surveys the development of graphical models …

This paper presents an overview of the topology of D-Wave's next-generation quantum
processors. It provides examples of minor embeddings and discusses performance of …

The development of small-scale quantum devices raises the question of how to fairly assess
and detect quantum speedup. Here, we show how to define and measure quantum speedup …

Quantum technology is maturing to the point where quantum devices, such as quantum
communication systems, quantum random number generators and quantum simulators may …

A general framework for constructing and using probabilistic models of complex systems that
would enable a computer to use available information for making decisions. Most tasks …

Constraint programming is a powerful paradigm for solving combinatorial search problems
that draws on a wide range of techniques from artificial intelligence, computer science …

Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and
reduce the realm of possibilities to effectively focus on the possible, allowing for a natural …

Handbook of Knowledge Representation describes the essential foundations of Knowledge
Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …