Zobrazeno 1 - 10
of 106
pro vyhledávání: '"KASMARIK, KATHRYN"'
Autor:
Tran, Vu Phi, Perera, Asanka G., Garratt, Matthew A., Kasmarik, Kathryn, Anavatti, Sreenatha G.
This paper introduces a state-machine model for a multi-modal, multi-robot environmental sensing algorithm tailored to dynamic real-world settings. The algorithm uniquely combines two exploration strategies for gas source localization and mapping: (1
Externí odkaz:
http://arxiv.org/abs/2407.01308
Radio source localization can benefit many fields, including wireless communications, radar, radio astronomy, wireless sensor networks, positioning systems, and surveillance systems. However, accurately estimating the position of a radio transmitter
Externí odkaz:
http://arxiv.org/abs/2312.03493
Multi-objective Markov decision processes are a special kind of multi-objective optimization problem that involves sequential decision making while satisfying the Markov property of stochastic processes. Multi-objective reinforcement learning methods
Externí odkaz:
http://arxiv.org/abs/2308.09734
This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms: (1) coverage path planning using variable formations and (2) collabo
Externí odkaz:
http://arxiv.org/abs/2306.04083
Neural-based learning agents make decisions using internal artificial neural networks. In certain situations, it becomes pertinent that this knowledge is re-interpreted in a friendly form to both the human and the machine. These situations include: w
Externí odkaz:
http://arxiv.org/abs/2204.00272
Publikováno v:
In Engineering Applications of Artificial Intelligence January 2025 139 Part A
This paper proposes a novel swarm-based control algorithm for exploration and coverage of unknown environments, while maintaining a formation that permits short-range communication. The algorithm combines two elements: swarm rules for maintaining a c
Externí odkaz:
http://arxiv.org/abs/2111.14295
Autor:
Kasmarik, Kathryn1 (AUTHOR) k.merrick@adfa.edu.au, Khani, Mahtab1 (AUTHOR) m.mohtasham_khani@unsw.edu.au, Abpeikar, Shadi2 (AUTHOR) s.abpeikar@unsw.edu.au, Barlow, Michael1 (AUTHOR) m.barlow@unsw.edu.au, Carter, Olivia3 (AUTHOR) ocarter@unimelb.edu.au, Irish, Muireann4 (AUTHOR) muireann.irish@sydney.edu.au
Publikováno v:
ACM Computing Surveys. Jan2025, Vol. 57 Issue 1, p1-26. 26p.
It is well-known that information loss can occur in the classic and simple Q-learning algorithm. Entropy-based policy search methods were introduced to replace Q-learning and to design algorithms that are more robust against information loss. We conj
Externí odkaz:
http://arxiv.org/abs/2006.14795
Autor:
Nguyen, Hung The, Nguyen, Tung Duy, Tran, Vu Phi, Garratt, Matthew, Kasmarik, Kathryn, Anavatti, Sreenatha, Barlow, Michael, Abbass, Hussein A.
The control and guidance of multi-robots (swarm) is a non-trivial problem due to the complexity inherent in the coupled interaction among the group. Whether the swarm is cooperative or non-cooperative, lessons can be learnt from sheepdogs herding she
Externí odkaz:
http://arxiv.org/abs/2004.11543