TY - JOUR
AU - 
AB - The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) Distributed Situation Awareness for Multi-agent Mission in Dynamic Environments: A Case Study of Multi-UAVs Wildfires Searching Sagir Muhammad Yusuf and Chris Baber School of Computer Science, University of Birmingham, B15 2TT, Edgbaston, Birmingham, United Kingdom smy870@student.bham.ac.uk, c.baber@bham.ac.uk Abstract entities) will only have a partial view of the situation (due to their location, sensor data, and knowledge). The implication This thesis focuses attention on achieving Distributed Sit- is that ‘situation awareness’ need not reside in all agents in uation Awareness (DSA) with minimal resources (energy, a system but comes from the combination of views. In order processing cost, etc.) using small low-capacity agents (e.g., to draw together these views, one can either create a com- UAVs) coordinated in a decentralised fashion while conduct- munications network in which all agents share and update ing searching activity. This is in contrast to the existing works each others’ views, or assume that collation of information involving convoluted communication and information pro- occurs in a scheduled and structured manner. For this lat- cessing. ter, one might assume that reporting (from UAVs) would not be continuous, that not all UAVs will need to know (nor be Introduction 
TI - Distributed Situation Awareness for Multi-agent Mission in Dynamic Environments: A Case Study of Multi-UAVs Wildfires Searching
JF - Proceedings of the AAAI Conference on Artificial Intelligence
DO - 10.1609/aaai.v35i18.17867
DA - 2021-05-18
UR - https://www.deepdyve.com/lp/unpaywall/distributed-situation-awareness-for-multi-agent-mission-in-dynamic-aBmXRJCG2e
DP - DeepDyve
ER -