Optimal allocation and scheduling of demand in deregulated energy markets

Today, telecom operators face a threefold challenge: a social challenge dealing with the evolution of the consumer lifestyle, a technological challenge dealing with ever changing ICT trends and a business challenge dealing with the need for innovative business models. This paper introduces an idea of group-oriented services, a special type of personalized telecom services, as a possible solution for all three of these challenges. A proof-of-concept service, called Agent-Based Mobile Content Brokerage, is presented and elaborated with the aim to demonstrate a shift towards consumer-managed relationships, a novel provisioning paradigm within the telecom industry.

Group-oriented services: a shift towards consumer-managed relationships in the telecom industry

The deregulation of the electricity industry in many countries has created a number of marketplaces in which producers and consumers can operate in order to more effectively manage and meet their energy needs. To this end, this thesis develops a new model for electricity retail where end-use customers choose their supplier from competing electricity retailers. The model is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This model prevents strategic bidding and allows the auctioneer to maximise its payoff. Furthermore, we develop optimal single-item and multiitem algorithms for winner determination in such auctions that are significantly less complex than those currently available in the literature. Nevertheless, the consumption of the energy of each singular auctioneer has to be regulated and adapted to the submitted bids in order to maximise the payoff. To this extent, this work models the constellation of energy consuming devices as a distributed constraint optimisation problem (dCOP). However, to operate within this problem domain, dCOP algorithms must be complete, work with global cost functions and complete solutions, and, currently, there are no dCOP algorithms that fulfil these conditions. Therefore, this thesis develops a novel optimal dCOP algorithm, called COBB (constraint optimisation by broadcasting), and, additionally, adapt state-of-the-art counterparts to our domain. Empirical comparisons show that COBB clearly outperforms all of them. Finally, this work outlines effective strategies to reduce the network overload caused by broadcasting to maintain it into a range where it is a reasonable trade-off for COBB’s efficiency.

D I S S E R T A T I O N Electron Stimulated Desorption of Condensed Gases on Cryogenic Surfaces ausgefzum Zwecke der Erlangung des akademischen Grades eines Doktors der technischen Wissenschaften unter der Leitung von

Interaction of Agent in E-Business: A Look at Different Sources

The above paper presents a rather complicated mechanism allowing fuzzy evidence to be aggregated when fuzzy inferences are made about the same fuzzy variable by different rules. The purpose of this com- ment is to present that the FuzzyCLIPS address this problem in simpler way.

Comments on "FuzzyShell: A Large-Scale Expert System Shell Using Fuzzy Logic for Uncertainty Reasoning"

Increasingly many systems are being conceptualised, designed and implemented as marketplaces in which autonomous software entities (agents) trade services. These services can be commodities in e-commerce applications or data and knowledge services in information economies. In such systems, dynamic pricing through some form of negotiation or auction protocol is becoming the norm for many goods and customers. Thus, negotiation capabilities for software agents are a central concern. Specifically, agents need to be able to prepare bids for and evaluate offers on behalf of the parties they represent with the aim of obtaining the maximum benefit for their users. They do this according to some negotiation strategies. However, in many cases, determining which strategy to employ is a complex decision making task because of the inherent uncertainty and dynamics of the situation. To this end, this thesis is concerned with developing bidding strategies for a range of auction contexts. In this thesis, we focus on a number of agent mediated e-commerce settings. In particular, we design novel strategies for the continuous double auctions, for the international trading agent competition that involves multiple interrelated auctions, and for multiple overlapping English auctions. All these strategies have been empirically benchmarked against the main other models that have been proposed in the literature and, in all cases, our strategies have been shown to be superior in a wide range of circumstances. Moreover all our models exploit soft computing methods, in particular fuzzy logic and neuro-fuzzy techniques. Such methods are used to cope with the significant degrees of uncertainty that exist in on-line auctions and we show they are a practical solution method for this class of applications. In developing such strategies we believe this work represents an important step towards realising the full potential of bidding agents in e-commerce scenarios.

Minghua He

Papers

Designing Bidding Strategies for Autonomous Trading Agents