Sciweavers

Share
ATAL
2009
Springer

A self-organizing neural network architecture for intentional planning agents

9 years 5 months ago
A self-organizing neural network architecture for intentional planning agents
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can be accommodated through multidirectional activations accross different modalities of patterns. The network seamlessly interleaves planning and learning processes towards achieving the goal. Case studies and experiments shows that the model can be used to execute, plan, and capture plan...
Budhitama Subagdja, Ah-Hwee Tan
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ATAL
Authors Budhitama Subagdja, Ah-Hwee Tan
Comments (0)
books