Learning from experience in Hangzhou: WLCE leisure experience research opportunity

Engaging Citizens and Patients in Health Research: Learning from Experience

Learning Conflicts from Experience

Multi-agent path finding has been proven to be a PSPACE-hard problem. Generating such a centralised multi-agent plan can be avoided, by allowing agents to plan their paths separately. However, this results in an increased number of collisions and agents must replan frequently. In this paper we present a framework for multi-agent path planning, which allows agents to plan independently and solve...

Learning from Experience, Simply

There is substantial academic interest in modeling consumer experiential learning. However, (approximately) optimal solutions to forward-looking experiential learning problems are complex, limiting their behavioral plausibility and empirical feasibility. We propose that consumers use cognitively simple heuristic strategies. We explore one viable heuristic – index strategies, and demonstrate tha...

Learning from experience

1 Learning from experience Innovation in the NHS is now being driven regionally by strategic health authorities. Learning how other national and international organisations have approached, planned and embedded innovation will help SHAs foster a culture of innovation. This overview outlines key evidence about what has worked well and what has been challenging elsewhere in adopting and dissemina...

Learning from Scarce Experience

Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each change of the target policy, its value is estimated from the results of following that very policy. This requires a large number of interactions with the environment as different polices are considered. We present a fa...