Internal Simulation of an Agent`s Intentions
(2013) Biologically Inspired Cognitive Architectures 2012: Third Annual Meeting of the BICA Society 196. p.175-176- Abstract
- We present the Associative Self-Organizing Map (A-SOM) and propose that it could be used to predict an agent's intentions by internally simulating the behaviour likely to follow initial movements. The A-SOM is a neural network that develops a representation of its input space without supervision, while simultaneously learning to associate its activity with an arbitrary number of additional (possibly delayed) inputs. We argue that the A-SOM would be suitable for the prediction of the likely continuation of the perceived behaviour of an agent by learning to associate activity patterns over time, and thus a way to read its intentions.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3437751
- author
- Johnsson, Magnus LU and Buonamente, Miriam LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Biologically Inspired Cognitive Architectures 2012 (Advances in Intelligent Systems and Computing)
- editor
- Chella, Antonio
- volume
- 196
- pages
- 175 - 176
- publisher
- Springer
- conference name
- Biologically Inspired Cognitive Architectures 2012: Third Annual Meeting of the BICA Society
- conference location
- Palermo, Italy
- conference dates
- 2012-10-31 - 2012-11-03
- external identifiers
-
- wos:000313923100032
- scopus:84870772018
- ISSN
- 2194-5357
- ISBN
- 978-3-642-34274-5
- DOI
- 10.1007/978-3-642-34274-5_32
- project
- Thinking in Time: Cognition, Communication and Learning
- language
- English
- LU publication?
- yes
- id
- 7f9e5a68-3c8d-4a08-9fc0-299b482f36f2 (old id 3437751)
- date added to LUP
- 2016-04-01 15:00:28
- date last changed
- 2022-01-28 03:37:34
@inproceedings{7f9e5a68-3c8d-4a08-9fc0-299b482f36f2, abstract = {{We present the Associative Self-Organizing Map (A-SOM) and propose that it could be used to predict an agent's intentions by internally simulating the behaviour likely to follow initial movements. The A-SOM is a neural network that develops a representation of its input space without supervision, while simultaneously learning to associate its activity with an arbitrary number of additional (possibly delayed) inputs. We argue that the A-SOM would be suitable for the prediction of the likely continuation of the perceived behaviour of an agent by learning to associate activity patterns over time, and thus a way to read its intentions.}}, author = {{Johnsson, Magnus and Buonamente, Miriam}}, booktitle = {{Biologically Inspired Cognitive Architectures 2012 (Advances in Intelligent Systems and Computing)}}, editor = {{Chella, Antonio}}, isbn = {{978-3-642-34274-5}}, issn = {{2194-5357}}, language = {{eng}}, pages = {{175--176}}, publisher = {{Springer}}, title = {{Internal Simulation of an Agent`s Intentions}}, url = {{http://dx.doi.org/10.1007/978-3-642-34274-5_32}}, doi = {{10.1007/978-3-642-34274-5_32}}, volume = {{196}}, year = {{2013}}, }