In 1950, Turing suggested that intelligent behavior might require “a departure from the completely disciplined behavior involved in computation”, but nothing that a digital computer could not do. In this paper, I want to explore Turing’s suggestion by asking what it is, beyond computation, that intelligence might require, why it might require it and what knowing the answers to the 6rst two ques...

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as "offloading computation from the brain to the body," where the body is said to perform "morphological computation." Our investigation of four characteristic cases of morphological computation in animals and robots shows that the "offloading" perspective is misleading. Actually, th...

Computation used to be synonymous to calculation. Now computation is what computers do, and it has become the engine of science. Increasingly more powerful machines push the limit of what is known in many fields. Intelligent systems compete with humans and win. Even natural systems like cells or the brain are occasionally modeled in computational terms. Is this use of computation still consiste...

Edge intelligence, a new paradigm to accelerate artificial intelligence (AI) applications by leveraging computing resources on the network edge, can be used improve intelligent transportation systems (ITS). However, due physical limitations and energy-supply constraints, powers of edge equipment are usually limited. High altitude platform station (HAPS) considered promising extension computing....

We study the use of model checking techniques for the generation of test sequences. Given a formal model of the system to be tested, one can formulate test purposes. A model checker then derives test sequences that fulfill these test purposes. The method is demonstrated by applying it to a specification of an Intelligent Network with two features.

One of the nmin png,~lems ,ff interval computations is, given a functhm f ( x l . . . . . xn) and n intervals x i , . . . , x n , to compute the range y = f ( x l ~ , . . . , x n ) . This problem is feasible for linear fttnction s f , but for genetic Ixdynomials, it is known to be cmHputationally intractable. Becau~ of that, traditional interval techniques usually compute the e~wJa~,re ,ff y , ...

In some real systems, e.g., sensor networks, individual agents will often need to form coalitions to accomplish complex tasks. Due to communication or computation constrains, it is infeasible for agents to directly interact with all other peers to form coalitions. Most current coalition formation works, however, overlooked this aspect. Those works usually did not provide an explicitly modeled a...

Usually, expert systems use numbers to describe the experts’ degrees of belief in their statements. In practice, however, it is difficult to assign an exact numerical value to the expert’s degree of belief. At best, we can get an interval of possible values. This fact leads to the use of interval-valued degrees of belief. When intervals are used to describe degrees of belief, then computations ...

Paul MacLean, following the evolutionary scheme, proposed the idea of “triune–brain,” in which the cortex is organised into three layers. He proposed that the three layers are responsible for instinctual behaviour, the motivational and emotional influences, and the rational influences on decision making, respectively. We borrow this metaphor of triune–brain to propose a unifying viewpoint for b...

Compressive sensing can minimize the collection of redundant data in the acquisition step. However, it requires a huge amount of storage and creates a tremendous computation burden due to the size of random measurement matrix in compressive sensing theory for big data collection. The separable compressive sensing theory uses two-dimensional separable random measurement matrixes instead of a hug...