New mathematical model can measure political party power
A new algorithm developed by ECS researcher Dr Edith Elkind can be used to predict political power balances.
In a paper entitled: 'Manipulating the Quota in Weighted Voting Games' published in the Proceedings of the Association for the Advancement of Artificial Intelligence conference, Dr Elkind and her co-authors describe how a mathematical model developed to describe voting in a parliament can facilitate decision-making among groups of computerised agents.
'Agents tend to form coalitions in much the same way as political parties,' she said. 'So I thought it would be interesting to look at what would happen to the balance of power if you change the number of votes needed to make a decision.'
In the paper, Dr Elkind, who is part of ECS’s Intelligence, Agents, Multimedia Group, illustrates that the power of a political party is very much dependent on whether bills are passed by a simple majority (50 per cent of all votes) or a qualified majority (two-thirds of all votes).
She believes that the same is true of autonomous agents, and that by applying the model to these scenarios, possible outcomes can be predicted.
'We can quantify the change in the balance of power caused by changing the voting threshold, like requiring a two-thirds majority to pass a bill rather than a 50 percent majority.'