Szczegóły publikacji
Opis bibliograficzny
Training example generation method for supervised learning agents in sequential scenarios / Paweł Stobiecki, Bartłomiej ŚNIEŻYŃSKI // Procedia Computer Science [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1877-0509. — 2014 — vol. 35, s. 44–53. — Bibliogr. s. 53, Abstr. — KES2014 : 18th international conference on Knowledge-Based and Intelligent Information & Engineering Systems : Gdynia, Poland, September 15–17, 2014
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 95333 |
|---|---|
| Data dodania do BaDAP | 2016-02-03 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.procs.2014.08.083 |
| Rok publikacji | 2014 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Procedia Computer Science |
Abstract
In this paper we propose a method of training example generation from agent's experience, which is suitable for sequential scenarios. The experience consists of the agent's observations and its action records. Examples generated are used by the agent to learn a classifier, which is used to make decisions about its strategy in the following problem instances. The method is tested in a Sovereign environment, which is an economics simulation created to test agent-based learning. Experimental results show that an agent using the proposed methods is able to learn and achieves better results than random and heuristic agents.
