Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing

This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory mid-point pricing. Buyers and sellers use Roth-Erev individual reinforcement learning to determine their price and quantity offers in each auction round. It is shown that market microstructure is strongly predictive for the relative market power of buyers and sellers, and that high market efficiency is generally attained. These findings are robust for tested changes in individual learning parameters. It is also shown that similar relative market power findings are obtained if the electricity buyer and seller populations instead each engage in social mimicry learning via a genetic algorithm. However, market efficiency is substantially reduced.Wholesale electricity market, Electricity restructuring, Double auction, Market power, Efficiency, Concentration, Capacity, Agent-based computational economics, Roth-Erev reinforcement learning, Genetic algorithm social learning.

Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing

This study reports experimental market power and efficiency outcomes for a computational wholesale electricity market operating in the short run under systematically varied concentration and capacity conditions. The pricing of electricity is determined by means of a clearinghouse double auction with discriminatory midpoint pricing. Buyers and sellers use a modifed Roth-Erev individual reinforcement learning algorithm to determine their price and quantity offers in each auction round. It is shown that high market efficiency is generally attained, and that market microstructure is strongly predictive for the relative market power of buyers and sellers independently of the values set for the reinforcement learning parameters. Results are briefly compared against results from an earlier electricity study in which buyers and sellers instead engage in social mimicry learning via genetic algorithms. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htmagent-based computational economics; Wholesale electricity market; restructuring; repeated double auction; market power; efficiency; concentration; capacity; individual reinforcement learning; genetic algorithm social learning

The Atom of Knowledge: Using Info Triples to Build Info Graphs - Short Version

Abstract—As Artificial Intelligence is developed to be more useful and used, expressing knowledge in a generalised, machine friendly way becomes important. In this article we start with an empty universe and from there set out to find the simplest possible structure to represent knowledge. We claim to find the atom of knowledge and give it the formal name Info Triple. Furthermore we use this structure to build a special kind of graph which we call Info Graph. The Info Graph can be used to model information context. We discuss the maths behind Info Graphs and compare it to existing standards. We compare the intended use of Info Graphs with the way graphs are currently used to model graph databases. Finally we conclude that the use of Info Graphs makes the models more generalised and therefore better suited for AI readers. Thus we believe our findings can serve as a valuable theoretical backbone for future knowledge base implementations. Keywords—AI, graphs, info graph, info triple, information modelling, knowledge bas

Increasingly Equalized? A Study of Part-Time Work in ‘Old’ and ‘New’ Part-Time Work Regimes

Recent debates on equalization of part-time work alongside full-time work stress the importance of high quality part-time jobs. This paper compares equalization in banking in three countries: two `old´ part-time work regimes, Norway and Sweden, and Ireland, where part-time work started to increase more recently. Banking is particularly interesting as a sector with a high proportion of female employment and good working conditions. One main interest is the role of regulations and how they are enforced at company level. The analysis shows that part-time work in the Nordic countries is normalized in terms of access and general work conditions, while in Ireland access is more restricted. Career opportunities are, however, restricted in all three countries. This paper argues that further equalization may be hindered by `soft´ regulations and a gradual normalization process that also normalizes disadvantages associated with part-time work and the category of the `working mother´