Planning and Doing Things

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.I was interested in computers by the age of 15 and gave talks on them at school. I attended evening classes a couple of years later while still at school travelling on the bus for an hour in the evening to a college in Leeds to learn programming (in COBOL!). Computers at that time filled a room, you submitted your exercises on punched card and got the results the following day. I built my first AI planner over 35 years ago. I’d already been on an early AI course at Lancaster University where the language of choice for teaching a range of topics was POP-2 and wanted to do a Summer project to create a problem solver. With support from Donald Michie and his team at Edinburgh I tried to create a Graph Traverser along the lines they were working on. Boy, am I glad I got involved with Computers, AI and planning technology

Generating Bayes-Nash equilibria to design autonomous trading agents.

This paper presents a methodology for designing trading agents for complex games. We compute, for the first time, Bayes-Nash equilibria for firstprice single-unit auctions and mth-price multi-unit auctions, when the auction has a set of possible closing times, one of which is chosen randomly for the auction to end at. To evaluate this approach we used our analysis to generate strategies for the International Trading Agent Competition. One of these was evaluated as the best overall and was subsequently used very successfully by our agent WhiteBear in the 2005 competition

Generating Bayes-Nash equilibria to design autonomous trading agents

This paper presents a methodology for designing trading agents for complex games. We compute, for the first time, Bayes-Nash equilibria for firstprice single-unit auctions and m th-price multi-unit auctions, when the auction has a set of possible closing times, one of which is chosen randomly for the auction to end at. To evaluate this approach we used our analysis to generate strategies for the International Trading Agent Competition. One of these was evaluated as the best overall and was subsequently used very successfully by our agent WhiteBear in the 2005 competition.