AI Communications - Volume 28, issue 4

Article Type: Other

Citation: AI Communications, vol. 28, no. 4, pp. 605-605, 2015

Authors: Mihailescu, Radu-Casian | Ossowski, Sascha

Article Type: Research Article

Abstract: Fundamental changes in the electrical energy sector are drawing on serious implications leading to high heterogeneity in both supply and demand. One focal point in transitioning to the smart grid vision is the liberalization and deregulation of electricity markets, which are undergoing a transformation towards accommodating a more decentralized and sustainable provision of energy. As the number of traders in the market is increasing steadily and the trading activities are becoming more complex, the energy markets are becoming more exposed to potential fraud. In this paper we address the problem of detecting collusive behavior, where a group of individual …traders act together, inconsistently with the competitive model, to artificially manipulate the market and elicit illegal profits. We investigate collusion attacks in the energy market and propose a novel mechanism, showing the effectiveness and practical applicability of our method to real scenarios. Thus, while economic analysis does not imply proving guilt, it can be instrumental in making decisions about identifying market participants worthy of closer inspection from appointed antitrust authorities. Show more

Keywords: Collusion detection, energy markets, smart grids

DOI: 10.3233/AIC-140625

Citation: AI Communications, vol. 28, no. 4, pp. 607-616, 2015

Authors: Vouros, George

Article Type: Research Article

Abstract: Agents in inherently distributed and open settings cannot be assumed to share an agreed ontology of their common task environment. To interact effectively, these agents need to establish semantic correspondences between their ontology elements. However, the correspondences computed by two agents may differ due to (a) differences in their ontologies, (b) different alignment methods used, and due to (c) different information one makes available to the other. Although semantic coordination methods have already been proposed for the computation of subjective correspondences between agents (i.e. correspondences from the viewpoint of a specific agent), this paper proposes a decentralized method for communities, …groups and arbitrarily formed networks of interconnected agents to reach semantic agreements on subjective ontology elements’ correspondences, via belief propagation: Agents detect disagreements on correspondences via feedback they receive from others, and they revise their decisions with respect to their preferences on correspondences and the semantics of ontological specifications. This work addresses this problem by means of a distributed extension of the max-plus algorithm. Experimental results from a large number of networks of varying complexity show the strengths of the proposed approach. Show more

Keywords: Ontology alignment, belief propagation, semantic agreements, agreement technologies

DOI: 10.3233/AIC-140624

Citation: AI Communications, vol. 28, no. 4, pp. 617-634, 2015

Article Type: Other

Citation: AI Communications, vol. 28, no. 4, pp. 635-635, 2015

Authors: Sorkhi, Maryam | Hashemi, Sattar

Article Type: Research Article

Abstract: Discovering an effective team of experts toward accomplishing the specific task in social networks has been considered in many real projects. The communication and collaboration among the members and the small cardinality of the team are in the opposite direction to success of the projects. In this paper, we show that the type of a similarity function is also impressive. Its importance is revealed on determining what similar or dissimilar experts should be selected or rejected in the process of the assignment. Considering the graph of underlying social network as conceptual social networking websites, we attribute the team formation problem …as a vertices similarity environment based on their common neighbors regarding their co-authored papers. Also, the implicit similarities are used with respect to inattention of additional intermediates between any two nodes in the graph. In addition, taking inspiration from human–human interactions, using just the implicit vertex similarities propose a collaborative recommendation that is based on the team formation framework. They can also identify effectors in social networks established by the structural equivalence relation. Thus, they make the algorithm faster on searching for members of the team. Moreover, the proficiency similarity measures of authors are considered as their potential characteristics that measure their skillfulness level and real contribution corresponding to the required skill. The combination of similarity measures in the cost function causes the algorithm to search the more effective team specially in equal situations. The experimental results on DBLP co-authorship graph show the effectiveness of using the new similarity measures in the proposed method. Show more

Keywords: Social networks, team of experts, similarity measures

DOI: 10.3233/AIC-140628

Citation: AI Communications, vol. 28, no. 4, pp. 637-654, 2015

Authors: Afrati, Foto N. | Fotakis, Dimitris | Vasilakopoulos, Angelos

Article Type: Research Article

Abstract: AI systems typically make decisions and find patterns in data based on the computation of aggregate and specifically sum functions, expressed as queries, on data’s attributes. This computation can become costly or even inefficient when these queries concern the whole or big parts of the data and especially when we are dealing with big data. New types of intelligent analytics require also the explanation of why something happened. In this paper we present a randomised algorithm that constructs a small summary of the data, called Aggregate Lineage, which can approximate well and explain all sums with large values in …time that depends only on its size. The size of Aggregate Lineage is practically independent on the size of the original data. Our algorithm does not assume any knowledge on the set of sum queries to be approximated. Show more

Keywords: Artificial intelligence, databases, aggregate queries, database lineage, query approximation, randomised algorithms

DOI: 10.3233/AIC-140647

Citation: AI Communications, vol. 28, no. 4, pp. 655-663, 2015

Authors: Alcázar, Vidal | Fernández, Susana | Borrajo, Daniel | Veloso, Manuela

Article Type: Research Article

Abstract: Rapidly-exploring Random Trees (RRTs) are data structures and search algorithms designed to be used in continuous path planning problems. They are one of the most successful state-of-the-art techniques in motion planning, as they offer a great degree of flexibility and reliability. However, their use in other fields in which search is a commonly used approach has not been thoroughly analyzed. In this work we propose the use of RRTs as a search algorithm for automated planning. We analyze the advantages and disadvantages that this approach has over previously used search algorithms and the challenges of adapting RRTs for implicit and …discrete search spaces. Show more

Keywords: Automated planning, heuristic search, random sampling

DOI: 10.3233/AIC-150658

Citation: AI Communications, vol. 28, no. 4, pp. 665-681, 2015

Authors: Sutcliffe, Geoff

Article Type: Research Article

Abstract: The CADE ATP System Competition (CASC) is an annual evaluation of fully automatic, classical logic Automated Theorem Proving (ATP) systems. CASC-J7 was the nineteenth competition in the CASC series. Twenty-four ATP systems and system variants competed in the various competition and demonstration divisions. An outline of the competition design, and a commentated summary of the results, are presented.

Keywords: Automated theorem proving, competition

DOI: 10.3233/AIC-150668

Citation: AI Communications, vol. 28, no. 4, pp. 683-692, 2015

Authors: Geetha, D.D. | Nalini, N. | Biradar, Rajashekhar C.

Article Type: Research Article

Abstract: Wireless Sensor Networks (WSNs) have been extensively used in various applications such as environmental monitoring, industrial monitoring, agriculture, green house monitoring, structural monitoring, passive localization, tracking and battlefield surveillance. Sensor nodes in these applications are required to sense and process the physical conditions like temperature, pressure, humidity, rainfall, fog, etc. and route the data to a predefined base station or a sink node. In most of these applications, sensor nodes are deployed in public domain and they are prone to be attacked by many types of attacks where in the data confidentiality, integrity and authentication are compromised. Some times, it …is difficult to correctly locate the compromised data unless we use autonomous third party that uses intelligent software techniques to safeguard our data and correctly means route it to destined party. In this paper, we propose a Trust based Neighbor Identification in Wireless Sensor Networks (TNIWSN) using agents to identify trustworthy nodes in a network. The trusted neighbor identification is necessary for routing the data through trustworthy neighbors and avoid untrusted neighbors that are compromised by various threats. The proposed scheme operates in following phases. (1) Defining safeguard agency that consists of one static agent known as Safeguard Manager Agent (SMA) and one mobile agent known as Trusted Neighbor Agent (TNA) and a knowledge base. (2) Safeguard agency identifies trustworthy neighbor nodes using static and mobile agents by means of trust model that comprise of the probability model and Message Authentication Code (MAC) model. The probability model identifies trusted neighbors based upon the probabilities of trustworthiness of wireless channel and the trustworthiness of sensor node. MAC model encrypts the message using the two keys k 1 and k 2 are generated with k-ERF (Error Resilient Function) key generation process to ensure the trustworthiness of neighbors identified by the probability model. (3) MACs are dynamically computed by agents (either on sender node or on neighbor node) by generating keys with the help of k-ERF. (4) Agents effectively identify possible security threats on wireless channel and node. Simulation analysis shows that TNIWSN outperforms Neighbor based Malicious Node Detection (NMND) in Wireless Sensor Networks in terms of average success ratio and memory overhead. Show more

Keywords: Wireless Sensor Networks, trusted neighbors, software agents, error resilient function, message authentication code

DOI: 10.3233/AIC-150673

Citation: AI Communications, vol. 28, no. 4, pp. 693-708, 2015

Authors: Han, The Anh | Moniz Pereira, Luís | Santos, Francisco C. | Lenaerts, Tom

Article Type: Research Article

Abstract: The mechanisms of emergence and evolution of cooperation in populations of abstract individuals, with diverse behavioral strategies in co-presence, have been undergoing mathematical study via evolutionary game theory, inspired in part on evolutionary psychology. Their systematic study resorts to simulation techniques, thus enabling the study of aforesaid mechanisms under a variety of conditions, parameters and alternative virtual games. The theoretical and experimental results have continually been surprising, rewarding and promising. In our recent work, we initiated the introduction, in such groups of individuals, of cognitive abilities inspired on techniques and theories of Artificial Intelligence, namely those pertaining to Intention Recognition, …Commitment and Apology (separately and jointly), encompassing errors in decision-making and communication noise. As a result, both the emergence and stability of cooperation become reinforced comparatively to the absence of such cognitive abilities. This holds separately for Intention Recognition, for Commitment and for Apology, and even more so when they are jointly engaged. Our presentation aims to sensitize the reader to these evolutionary game theory based issues, results and prospects, which are accruing in importance for the modeling of minds with machines, with impact on our understanding of the evolution of mutual tolerance and cooperation. Recognition of someone’s intentions, which may include imagining the recognition others have of our own intentions, and may comprise not just some error tolerance, but also a penalty for unfulfilled commitment though allowing for apology, can lead to evolutionary stable win/win equilibriums within groups of individuals, and perhaps amongst groups. The recognition and the manifestation of intentions, plus the assumption of commitment – even whilst paying a cost for putting it in place – and the acceptance of apology, are all facilitators in that respect, each of them singly and, above all, in collusion. Show more

Keywords: Intention recognition, commitments, evolution of cooperation, apology, multi-agent systems, evolutionary game theory

DOI: 10.3233/AIC-150672

Citation: AI Communications, vol. 28, no. 4, pp. 709-715, 2015