A project for the Distributed Artificial Intelligence and Intelligent Agents course (FTN, University of Novi Sad), built using Java EE technologies and Angular.
- An agent framework that enables building multi-agent systems
- For demonstration purposes, there have been implemented two types of agents
- Chat application agents
- UserAgent
- UserHelperAgent
- Match outcome prediction agents
- CollectorAgent
- PredictorAgent
- MasterAgent
- Chat application agents
- When a prediction method is called, a master and predictor agent are started locally and a collector agent is started on each node in a cluster
- Each collector agent replies to the predictor agent with the match data for selected teams
- When data from all nodes has been forwarded to the predictor agent, it predicts the match outcome and sends the result to the master agent
- Master agent displays the result via websocket
- Java Enterprise Application
- Download Wildfly 11 application server
- Replace existing standalone-full-ha.xml file with the one provided here
- For the non-master cluster node you must provide master node name in the
connection.properties
file - Publish chat-ear.ear to
/standalone/deployments
folder
- Angular Application
- Download Node.js (version 14.15.0 used for development)
- Install Angular CLI (version 10.2.0 used for dvelopment)
- Navigate to
match-score-prediction-client
project and type:npm install
-
Java Enterprise Application
- Navigate to
/bin
folder of Wildfly and type:
standalone.bat -c standalone-full-ha.xml
./standalone.sh -c standalone-full-ha.xml
- Navigate to
-
Angular Application
- Navigate to
match-score-prediction-client
project and type:
ng serve
- To access system monitoring UI, type http://localhost:4200 in a browser
- To access match outcome prediction UI, type http://localhost:4200/prediction in a browser
- Navigate to