Comparing word fragment completion and cued recall with letter cues.

Cued recall with word stems as cues and fragment completion rely on different types of letter cues and also differ in the explicit–implicit nature of the retrieval orientation. Despite these differences, variables effective in one task may be effective in the other because both rely on letter cues. Two variables known to affect cued recall were manipulated: Lexical set size (number of words that fit the letter cue) and meaning set size (number of associates generated to the studied words). Across four experiments, subjects in each task were less likely to recover targets from larger lexical sets. However, meaning set size affected cued recall but not fragment completion. These results indicate that fragment completion and letter-cued recall are based on lexical search but that cued recall also involves a semantic search component. Furthermore, type of retrieval cue had a greater effect than type of retrieval orientation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Intentional inhibition in memory and hallucinations: Directed forgetting and updating.

Hallucinations have been recently associated with inhibitory deficits in memory. In this study, the authors investigated whether hallucinations were related to difficulties to inhibit irrelevant information from episodic memory (Experiment 1) and working memory (Experiment 2). In Experiment 1, a directed forgetting task was used. This task measures participants' ability to intentionally forget some recently learned material, when instructions indicate that it is no longer relevant. In Experiment 2, an updating task was used. This task requires participants to intentionally suppress irrelevant information from working memory. Results showed that patients with schizophrenia with hallucinations presented inhibitory deficits in the directed forgetting task and an increase in the number of intrusions in the updating task, compared to patients without hallucinations and healthy controls. No correlations were found between indices of inhibition and other general, negative or positive symptoms. These findings support the existence of an association between intentional inhibition in memory and hallucinations, and they suggest that problems to suppress memory representations can underlie hallucinations in schizophrenia. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Special issue on distributed computing and artificial intelligence

4:1! Google’s artificial intelligence (AI) program, AlphaGo, has won Go Master Lee Sedol in a best-of-five competition held in Korean March 9?15, 2016. Seen by many as a landmark moment for AI, the outcome did not come as a surprise, considering the excellent combination of 1920 CPUs with sophisticated AI algorithms, including neural networks and Monte Carlo tree search (Gibney, 2016; Silver et al., 2016). Indeed, research on distributed computing and artificial intelligence (DCAI) has matured during the last decade and many effective applications are now deployed, performing an increasingly important role in modern computer science, including the two most hyped technologies: Internet of Things and Big Data. Indeed, it is fair to say that the application of artificial intelligence in distributed environments is becoming an essential element of high added value and economic potential.     

Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks.     

REPLANNING MECHANISM FOR DELIBERATIVE AGENTS IN DYNAMIC CHANGING ENVIRONMENTS

This paper proposes a replanning mechanism for deliberative agents as a new approach to tackling the frame problem. We propose a beliefs desires and intentions (BDI) agent architecture using a case-based planning (CBP) mechanism for reasoning. We discuss the characteristics of the problems faced with planning where constraint satisfaction problems (CSP) resources are limited and formulate, through variation techniques, a reasoning model agent to resolve them. The design of the agent proposed, named MRP-Ag (most-replanable agent), will be evaluated in different environments using a series of simulation experiments, comparing it with others such as E-Ag (Efficient Agent) and O-Ag (Optimum Agent). Last, the most important results will be summarized, and the notion of an adaptable agent will be introduced.     

Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction

This work presents a system for automatically evaluating the interaction that exists between the atmosphere and the ocean’s surface. Monitoring and evaluating the ocean’s carbon exchange process is a function that requires working with a great amount of data: satellite images and in situ vessel’s data. The system presented in this study focuses on computational intelligence. The study presents an intelligent system based on the use of case-based reasoning (CBR) systems and offers a distributed model for such an interaction. Moreover, the system takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve over time. In order to resolve this problem, an intelligent environment has been developed, based on the use of CBR systems, which are capable of handling several goals, by constructing plans from the data obtained through satellite images and research vessels, acquiring knowledge and adapting to environmental changes. The artificial intelligence system has been successfully tested in the North Atlantic Ocean, and the results obtained will be presented in this study.     

Stereo Video Surveillance Multi-agent System: New Solutions for Human Motion Analysis

This article presents a distributed agent-based system that can process the visual information obtained by stereoscopic cameras. The system is embedded within a global project whose objective is to develop an intelligent environment for location and identification within dependent environments that merges with other types of technologies. In this kind of environments, vision algorithms are very costly and require a lot of time to produce a response, which is highly inconvenient since many applications can require action to be taken in real time. A multi-agent system (MAS) can automate the process of analyzing images obtained by cameras, and optimize the procedure. This study presents a MAS that can process stereoscopic images to detect and classify people by combining a series of novel techniques. The article shows in detail the combination of techniques used to perform the detection process. The process can be subdivided into human detection, human tracking, and human behavior understanding. With the addition of a case-based reasoning (CBR) model, the system can also incorporate reasoning capabilities. The system was tested under different conditions and environments.