Planning with neural networks and reinforcement learning
نویسنده
چکیده
planning with neural networks, time limits of discounted reinforcement learning Planning, taskability, Dyna-PI architectures Dyna-PI architectures: focussing, forward and backward planning, acting and (re)planning. Tested with... Ideas from problem solving and
منابع مشابه
Reinforcement Learning in Neural Networks: A Survey
In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...
متن کاملReinforcement Learning in Neural Networks: A Survey
In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...
متن کاملBeyond Simple Rule Extraction: Acquiring Planning Knowledge from Neural Networks
This paper discusses learning in hybrid models that goes beyond simple classification rule extraction from backpropagation networks. Although simple rule extraction has received a lot of research attention, we need to further develop hybrid learning models that learn autonomously and acquire both symbolic and subsymbolic knowledge. It is also necessary to study autonomous learning of both subsy...
متن کاملForward and Bidirectional Planning Based on Reinforcement Learning and Neural Networks in a Simulated Robot
Building intelligent systems that are capable of learning, acting reactively and planning actions before their execution is a major goal of artificial intelligence. This paper presents two reactive and planning systems that contain important novelties with respect to previous neural-network planners and reinforcement-learning based planners: (a) the introduction of a new component (“matcher”) a...
متن کاملMulticast Routing in Wireless Sensor Networks: A Distributed Reinforcement Learning Approach
Wireless Sensor Networks (WSNs) are consist of independent distributed sensors with storing, processing, sensing and communication capabilities to monitor physical or environmental conditions. There are number of challenges in WSNs because of limitation of battery power, communications, computation and storage space. In the recent years, computational intelligence approaches such as evolutionar...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001