Abstract
Despite high-profile successes in the field of Artificial Intelligence, machine-driven technologies still suffer important limitations, particularly for complex tasks where creativity, planning, common sense, intuition, or learning from limited data is required. These limitations motivate effective methods for human-machine collaboration. Our work makes two primary contributions. We thoroughly experiment with an artificial prediction market model to understand the effects of market parameters on model performance for benchmark classification tasks. We then demonstrate, through simulation, the impact of exogenous agents in the market, where these exogenous agents represent primitive human behaviors.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2304-2306 |
| Number of pages | 3 |
| Journal | Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS |
| Volume | 2023-May |
| State | Published - 2023 |
| Event | 22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023 - London, United Kingdom Duration: May 29 2023 → Jun 2 2023 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Software
- Control and Systems Engineering
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