**CODA Algorithm: An Immune Algorithm for Reinforcement Learning Tasks**

Daniel R. Ramirez Rebollo, Pedro Ponce Cruz and Arturo Molina

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/63570

### **Abstract**

This document presents the design of an algorithm that takes on its basis: reinforce‐ ment learning, learning from demonstration and most importantly Artificial Immune Systems. The main advantage of this algorithm named CODA (Cognition from Data). Is; it can learn from limited data samples- that is given a single example and the algorithm will create its own knowledge. The algorithm imitates from the Natural Immune System the clonal procedure for obtaining a repertoire of antibodies from a single antigen. It also uses the self-organised memory in order to reduce searching time in the whole action-state space by searching in specific clusters. CODA algorithm is presented and explained in detail in order to understand how these three principles are used. The algorithm is explained with pseudocode, flowcharts and block diagrams. The clonal/mutation results are presented with a simple example. It can be seen graphical‐ ly how new data that has a completely new probability distribution. Finally, the first application where CODA is used, a humanoid hand is presented. In this application the algorithm created affordable grasping postures from limited examples, creates its own knowledge and stores data in memory data in memory in order to recognise whether it has been on a similar situation.

**Keywords:** artificial immune system, artificial intelligence, neuroscience, biologically inspired algorithm, cognition
