Editing Distributed artificial intelligence (section)

==Approaches==
Two types of DAI has emerged: 
* In [[Multi-agent system]]s agents coordinate their knowledge and activities and reason about the processes of coordination. Agents are physical or virtual entities that can act, perceive its environment and communicate with other agents. The agent is autonomous and has skills to achieve goals. The agents change the state of their environment by their actions. There are a number of different coordination techniques.<ref name="Jennings">{{cite book |last1=Jennings |first1=Nick |editor1=Gregory M. P. O'Hare |editor2=N. R. Jennings |title=Foundations of Distributed Artificial Intelligence |date=1996 |publisher=Wiley |location=New York |chapter=Coordination Techniques for Distributed Artificial Intelligence |pages=187−210 |chapter-url=https://philpapers.org/rec/JENFOD |isbn=978-0-471-00675-6 |archive-date=1 November 2018 |archive-url=https://web.archive.org/web/20181101052328/https://eprints.soton.ac.uk/252187/1/FOUND%2DDAI%2DCOORD.pdf }}</ref>
* In distributed problem solving the work is divided among nodes and the knowledge is shared. The main concerns are task decomposition and synthesis of the knowledge and solutions.

DAI can apply a bottom-up approach to AI, similar to the [[subsumption architecture]] as well as the traditional top-down
approach of AI. In addition, DAI can also be a vehicle for [[emergence]].

===Challenges===
The challenges in Distributed AI are:
# How to carry out communication and interaction of agents and which communication language or protocols should be used.
# How to ensure the coherency of agents.
# How to synthesise the results among 'intelligent agents' group by formulation, description, decomposition and allocation.