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131878 articles
Proceedings Article

Discovering and characterizing Hidden Variables

Soumi Ray, Tim Oates
Theoretical entities are aspects of the world that cannot be sensed directly but that nevertheless are causally relevant. Scientifc inquiry has uncovered many such entities, such as black holes and dark matter. We claim that theoretical entities are omportant for the development of concepts within the...
Proceedings Article

On Super-Turing Computing Power and Hierarchies of Artificial General Intelligence Systems

Jiri Wiedermann
Using the contemporary view of computing exemplified by recent models and results from non-uniform complexity theory we investigate the computational power of artificial general intelligence systems (AGISs). We show that in accordance with the so-called Extended Turing Machine Paradigm such systems can...
Proceedings Article

What we might look for in an AGI benchmark

Brandon Rohrer
A benchmark in the ¯eld of Arti¯cial General Intelligence (AGI) would allow evaluation and comparison of the many computational intelligence algorithms that have been developed. In this paper I propose that an ideal benchmark would possess seven key characteristics: ¯tness, breadth, specificity, low...
Proceedings Article

Quantitative Spatial Reasoning for General Intelligence

Unmesh Kurup, Nicholas L. Cassimatis
One of the basic requirements of an intelligent agent is the ability to represent and reason about space. While there are a number of approaches for achieving this goal, the recent gains in efficiency of the Satisfiability approach have made it a popular choice. Modern propositional SAT solvers are efficient...
Proceedings Article

A Generic Adaptive Agent Architecture Integrating Cognitive and Affective States and their Interaction

Zulfiqar A. Memon, Jan Treur
In this paper a generic adaptive agent architecture is presented that integrates the interaction between cognitive and affective aspects of mental functioning, based on variants of notions adopted from neurological literature. It is discussed how it addresses a number of issues that have recurred in...
Proceedings Article

Cognitive Architecture Requirements for Achieving AGI

John E. Laird, Robert E. Wray III
We outline eight characteristics of the environments, tasks, and agents important for human-level intelligence. Treating these characteristics as influences on desired agent behavior, we then derive twelve requirements for general cognitive architectures. Cognitive-architecture designs that meet the...
Proceedings Article

Software Design of an AGI System Based on Perception Loop

Antonio Chella, Massimo Cossentino, Valeria Seidita
According to the externalist approach, subjective experience hypothesizes a processual unity between the activity in the brain and the perceived event in the external world. A perception loop therefore occurs among the brain's activities and the external world. In our work the metaphor of test is employed...

Granular Decision Tree and Evolutionary Neural SVM for Protein Secondary Structure Prediction

Anjum Reyaz-Ahmed, Yan-Qing Zhang, Robert W. Harrison
Pages: 343 - 352
A new sliding window scheme is introduced with multiple windows to form the protein data for SVM. Two new tertiary classifiers are introduced; one of them makes use of support vector machines as neurons in neural network architecture and the other tertiary classifier is a granular decision tree based...

Granular RBF NN Approach and Statistical Methods Applied to Modelling and Forecasting High Frequency Data

Dusan Marcek, Milan Marcek, Jan Babel
Pages: 353 - 364
We examine the ARCH-GARCH models for the forecasting of the bond price time series provided by VUB bank and make comparisons the forecast accuracy with the class of RBF neural network models. A limited statistical or computer science theory exists on how to design the architecture of RBF networks for...

Text Categorization Based on Topic Model

Shibin Zhou, Kan Li, Yushu Liu
Pages: 398 - 409
In the text literature, many topic models were proposed to represent documents and words as topics or latent topics in order to process text effectively and accurately. In this paper, we propose LDACLM or Latent Dirichlet Allocation Category LanguageModel for text categorization and estimate parameters...

Quorum-based Data Replication in Grid Environment

Rohaya Latip, Mohamed Othman, Azizol Abdullah, Hamidah Ibrahim, Nasir Sulaiman
Pages: 386 - 397
Replication is a useful technique for distributed database systems and can be implemented in a grid computation environment to provide a high availability, fault tolerant, and enhance the performance of the system. This paper discusses a new protocol named Diagonal Data Replication in 2D Mesh structure...

Intelligent Concepts for the Management of Information in Workflow Systems

Georg Peters, Roger Tagg
Pages: 332 - 342
Workflow systems are commonly used in industry, commerce and government. They provide computerized support for owners of repetitive, highly standardized business processes, with a means of controlling the execution of instances of those processes according to predefined process templates. However, many...

N-grams based feature selection and text representation for Chinese Text Classification

Zhihua Wei, Duoqian Miao, Jean-Hugues Chauchat, Rui Zhao, Wen Li
Pages: 365 - 374
In this paper, text representation and feature selection strategies for Chinese text classification based on n-grams are discussed. Two steps feature selection strategy is proposed which combines the preprocess within classes with the feature selection among classes. Four different feature selection...

Combining Resting-state fMRI and DTI Analysis for Early-onset Schizophrenia

Ming Ke, Hui Shen, Jintu Fan, Xing Huang, Zongtan Zhou, Xiaogang Chen, Dewen Hu
Pages: 375 - 385
We combined measures of resting-state functional magnetic resonance imaging and diffusion tensor imaging (DTI) to investigate alterations of function-structure relationships in patients with early-onset schizophrenia. DTI analysis revealed reduced fractional anisotropy in right frontal white matter....

On Knowledge Granulation and Applications to Classifier Induction in the Framework of Rough Mereology

Lech Polkowski, Piotr Artiemjew
Pages: 315 - 331
Knowledge granulation as proposed by Zadeh consists in making objects under discussion into classes called granules; objects within a granule are similar one to another to a satisfactory degree relative to a chosen similarity measure. Rough mereology as developed by Polkowski in a series of works is...

A Hybrid Artificial Immune Optimization Method

X. Wang, X.Z. Gao, S. J. Ovaska
Pages: 248 - 255
This paper proposes a hybrid optimization method based on the fusion of the Simulated Annealing (SA) and Clonal Selection Algorithm (CSA), in which the SA is embedded in the CSA to enhance its search capability. The novel optimization algorithm is also employed to deal with several nonlinear benchmark...

An Evolutionary Approach to Underwater Sensor Deployment

Erik F. Golen, Bo Yuan, Nirmala Shenoy
Pages: 184 - 201
Underwater sensor deployment for military surveillance is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors, as well as the exorbitant cost of the sensors. As a result, these sensors must be deployed as efficiently...

An Alternative Ranking Approach and Its Usage in Multi-Criteria Decision-Making

Cengiz Kahraman, A. Cagri Tolga
Pages: 219 - 235
In the process of fuzzy decision-making, ranking of fuzzy numbers is a necessity. The types of fuzzy numbers are triangular, trapezoidal, and L-R type. In the literature, there are many methods developed for ranking fuzzy numbers. These methods may produce different ranking results. Many of these methods...

Neural Networks Simulation of the Transport of Contaminants in Groundwater

Enrico Zio
Pages: 267 - 276
The performance assessment of an engineered solution for the disposal of radioactive wastes is based on mathematical models of the disposal system response to predefined accidental scenarios, within a probabilistic approach to account for the involved uncertainties. As the most significant potential...

Anisotropic Wavelet-Based Image Nearness Measure

James F. Peters, Leszek Puzio
Pages: 168 - 183
The problem considered in this article is how to solve the image correspondence problem in cases where it is important to measure changes in the contour, position, and spatial orientation of bounded regions. This article introduces a computational intelligence approach to the solution of this problem...

BMR: Benchmarking Metrics Recommender for Personnel issues in Software Development Projects

Angel Garcia-Crespo, Ricardo Colomo-Palacios, Juan Miguel Gomez-Berbis, Myriam Mencke
Pages: 256 - 266
This paper presents an architecture which applies document similarity measures to the documentation produced during the phases of software development in order to generate recommendations of process and people metrics for similar projects. The application makes a judgment of similarity of the Service...

A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems

Cengiz Kahraman, Orhan Engin, Mustafa Kerim Yilmaz
Pages: 236 - 247
In this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness...

Experiences with and Reflections on Text Summarization Tools

Shuha Liu
Pages: 202 - 218
Text summarization is a process of distilling the most important content from text documents. While human beings have proven to be extremely capable summarizers, computer based automatic abstracting and summarizing has proven to be extremely challenging tasks. In this paper we report our experience with...

Re-editing and Censoring of Detectors in Negative Selection Algorithm

X.Z. Gao, S. J. Ovaska, X. Wang
Pages: 298 - 311
The Negative Selection Algorithm (NSA) is a kind of novelty detection method inspired by the biological self/nonself discrimination principles. In this paper, we propose two new schemes for the detectors re-editing and censoring in the NSA. The detectors that fail to pass the negative selection phase...

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

Alp Ustundag
Pages: 277 - 287
Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales...

Optimal IP Assignment for Efficient NoC-based System Implementation using NSGA-II and MicroGA

Marcus Vinicius Carvalho da Silva, Nadia Nedjah, Luiza de Macedo Mourelle
Pages: 115 - 123
Network-on-chip (NoC) are considered the next generation of communication infrastructure, which will be omnipresent in most of industry, office and personal electronic systems. In platform-based methodology, an application is implemented by a set of collaborating intellectual properties (IPs) blocks....

Radial Basis Function Nets for Time Series Prediction

Abdelhamid Bouchachia
Pages: 147 - 157
This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive recurrent network proposed is based on the nonlinear...

Cellular Neural Networks-Based Genetic Algorithm for Optimizing the Behavior of an Unstructured Robot

Alireza Fasih, Jean Chamberlain Chedjou, Kyandoghere Kyamakya
Pages: 124 - 131
A new learning algorithm for advanced robot locomotion is presented in this paper. This method involves both Cellular Neural Networks (CNN) technology and an evolutionary process based on genetic algorithm (GA) for a learning process. Learning is formulated as an optimization problem. CNN Templates are...

The Influence of the Update Dynamics on the Evolution of the Cooperation

Carlos Grilo, Luis Correia
Pages: 104 - 114
We investigate the influence of the update dynamics on the evolution of cooperation. Three of the most studied games in this area are used: Prisoner’s Dilemma, Snowdrift and the Stag Hunt. Previous studies with the Prisoner’s Dilemma game reported that less cooperators survive with the asynchronous...

Networks of Mixed Canonical-Dissipative Systems and Dynamic Hebbian Learning

Julio Rodriguez, Max-Olivier Hongler
Pages: 140 - 146
We study the dynamics of a network consisting of N diffusively coupled, stable-limit-cycle oscillators on which individual frequencies are parametrized by ωk , k = 1, . . . , N. We introduce a learning rule which influences the ωk by driving the system towards a consensual oscillatory state in which...

Global Approximations to Cost and Production Functions using Artificial Neural Networks

Efthymios G. Tsionas, Panayotis G. Michaelides, Angelos T. Vouldis
Pages: 132 - 139
The estimation of cost and production functions in economics relies on standard specifications which are less than satisfactory in numerous situations. However, instead of fitting the data with a pre-specified model, Artificial Neural Networks (ANNs) let the data itself serve as evidence to support the...

Feature Extraction for the Prognosis of Electromechanical Faults in Electrical Machines through the DWT

J.A. Antonino-Daviu, M. Riera-Guasp, M. Pineda-Sanchez, J. Pons-Llinares, R. Puche-Panadero, J. Perez-Cruz
Pages: 158 - 167
Recognition of characteristic patterns is proposed in this paper in order to diagnose the presence of electromechanical faults in induction electrical machines. Two common faults are considered; broken rotor bars and mixed eccentricities. The presence of these faults leads to the appearance of frequency...
Proceedings Article

Self-Programming: Operationalizing Autonomy

Eric Nivel, Kristinn R. Thórisson
Lacking an operational definition of autonomy has considerably weakened the concept's impact in systems engineering. Most current "autonomous" systems are built to operate in conditions more or less fully described a priori, which is insufficient for achieving highly autonomous systems that adapt efficiently...
Proceedings Article

Embodiment: Does a laptop have a body?

Pei Wang
This paper analyzes the different understandings of "embodiment". It argues that the issue is not on the hardware a system is implemented in (that is, robot or conventional computer), but on the relation between the system and its working environment. Using an AGI system NARS as an example, the paper...
Proceedings Article

Parsing PCFG within a General Probabilistic Inference Framework

Arthi Murugesan, Nicholas L. Cassimatis
One of the aims of Artificial General Intelligence(AGI) is to use the same methods to reason over a large num- ber of problems spanning different domains. Therefore, advancing general tools that are used in a number of domains like language, vision and intention reading is a step toward AGI. Probabilistic...
Proceedings Article

Case-by-Case Problem Solving

Pei Wang
Case-by-case Problem Solving solves each occurrence, or case, of a problem using available knowledge and resources on the case. It is different from the traditional Algorithmic Problem Solving, which applies the same algorithm to all occurrences of all problem instances. Case-by-case Prob- lem Solving...
Proceedings Article

Relevance Based Planning: Why Its a Core Process for AGI

Eric B. Baum
Relevance Based Planning (RBP) is a general method that plans in interaction with a domain simulation and domain specialized procedures. I argue that exploitation of the properties of causality and Euclidean topology which hold in many domains is a critical inductive bias necessary if an AGI (or any...
Proceedings Article

In Search of Computational Correlates of Artificial Qualia

Antonio Chella, Salvatore Gaglio
In previous papers we presented a robot cognitive architecture organized in three computational areas. The subconceptual area is concerned with the processing of data coming from the sensors. In the linguistic area representation and processing are based on a logic-oriented formalism. The conceptual...
Proceedings Article

Bootstrap Dialog: A Conversational English Text Parsing and Generation System

Stephen L. Reed
A conversational English text parsing and generation system is described in which its lexicon and construction grammar rules are revised, augmented, and improved via dialog with mentors. Both the parser and generator operate in a cognitively plausible, incremental manner. Construction Grammar is well...
Proceedings Article

Achieving Artificial General Intelligence Through Peewee Granularity

Kristinn R. Thórisson, Eric Nivel
The general intelligence of any autonomous system must in large part be measured by its ability to automatically learn new skills and integrate these with prior skills. Cognitive architectures addressing these topics are few and far between ­ possibly because of their difficulty. We argue that architectures...
Proceedings Article

Hebbian Constraint on the Resolution of the Homunculus Fallacy Leads to a Network that Searches for Hidden Cause-Effect Relationships

András Lorincz
We elaborate on a potential resolution of the homunculus fallacy that leads to a minimal and simple auto-associative recurrent `reconstruction network' architecture. We insist on Hebbian constraint at each learning step executed in this network. We find that the hidden internal model enables searches...
Proceedings Article

Analytical Inductive Programming as a Cognitive Rule Acquisition Devise

Ute Schmid, Martin Hofmann, Emanuel Kitzelmann
One of the most admirable characteristic of the hu- man cognitive system is its ability to extract gener- alized rules covering regularities from example expe- rience presented by or experienced from the environ- ment. Humans' problem solving, reasoning and verbal behavior often shows a high degree of...
Proceedings Article

Project to Build Programs that Understand

Eric B. Baum
This extended abstract outlines a project to build computer programs that understand. Understanding a domain is defined as the ability to rapidly produce computer programs to deal with new problems as they arise. This is achieved by building a CAD tool that collaborates with human designers who guide...
Proceedings Article

Everyone's a Critic: Memory Models and Uses for an Artificial Turing Judge

W. Joseph MacInnes, Blair C. Armstrong, Dwayne Pare, George S. Cree, Steve Joordens
The Turing test was originally conceived by Alan Turing [20] to determine if a machine had achieved human-level intelligence. Although no longer taken as a comprehensive measure of human intelligence, passing the Turing test remains an interesting challenge as evidenced by the still unclaimed Loebner...
Proceedings Article

Program Representation for General Intelligence

Moshe Looks, Ben Goertzel
Traditional machine learning systems work with relatively flat, uniform data representations, such as feature vectors, time-series, and context-free grammars. However, reality often presents us with data which are best understood in terms of relations, types, hierarchies, and complex functional forms....
Proceedings Article

The China-Brain Project: Report on the First Six Months

Hugo de Garis, Ruiting Lian, Ben Goertzel, Wei Pan, Kehua Miao, Xiaodong Shi, Min Jiang, Lingxiang Zhen, Qinfang Wu, Minghui Shi, Jianyang Zhou
The "China Brain Project" is a 4 year (2008-2011), 10.5 million RMB research project to build China's first artificial brain, which will consist of 10,000- 50,000 neural net modules which are evolved rapidly in special FPGA hardware, downloaded one by one into a PC or supercomputer, and then connected...
Proceedings Article

The Importance of Being Neural-Symbolic ­ A Wilde Position

Pascal Hitzler, Kai-Uwe Kuhnberger
We argue that Neural-Symbolic Integration is a topic of central importance for the advancement of Artificial General Intelligence.