Dyna is a single-agent architectural framework that integrates learning, planning, and reacting. Well known instantiations of Dyna are Dyna-AC and Dyna-Q. Here a multiagent extension of Dyna-Q is presented. This extension, called M-Dyna-Q, constitutes a novel coordination framework that bridges the gap between plan-based and reactive coordination in multiagent systems. The paper summarizes the ...

Dyna planning is an efficient way of learning from real and imaginary experience. Existing tabular and linear Dyna algorithms are single-step, because an “imaginary” feature is predicted only one step into the future. In this paper, we introduce a multi-step Dyna planning that predicts more steps into the future. Multi-step Dyna is able to figure out a sequence of multi-step results when a real...

This paper describes a multiagent variant of Dyna-Q called M-Dyna-Q. Dyna-Q is an integrated single-agent framework for planning, reacting, and learning. Like DynaQ, M-Dyna-Q employs two key ideas: learning results can serve as a valuable input for both planning and reacting, and results of planning and reacting can serve as a valuable input to learning. M-Dyna-Q extends Dyna-Q in that planning...

This paper extends previous work with Dyna, a class of architectures for intelligent systems based on approximating dynamic programming methods. Dyna architectures integrate trial-and-error (reinforcement) learning and execution-time planning into a single process operating alternately on the world and on a learned model of the world. In this paper, I present and show results for two Dyna archi...

This is a summary of results with Dyna, a class of architectures for intelligent systems based on approximating dynamic programming methods. Dyna architectures integrate trial-and-error (reinforcement) learning and execution-time planning into a single process operating alternately on the world and on a learned forward model of the world. We describe and show results for two Dyna architectures,...

Weighted deduction with aggregation is a powerful theoretical formalism that encompasses many NLP algorithms. This paper proposes a declarative specification language, Dyna; gives general agenda-based algorithms for computing weights and gradients; briefly discusses Dyna-to-Dyna program transformations; and shows that a first implementation of a Dyna-to-C++ compiler produces code that is effici...

Weighted deduction with aggregation is a powerful theoretical formalism that encompasses many NLP algorithms. This paper proposes a declarative specification language, Dyna; gives general agenda-based algorithms for computing weights and gradients; briefly discusses Dyna-to-Dyna program transformations; and shows that a first implementation of a Dyna-to-C++ compiler produces code that is effici...

PURPOSE The aim of our study was to determine whether using C-arm CT (DYNA CT) during hepatic arteriography imaging assists in TACE treatment. MATERIALS AND METHODS 138 patients with HCC, 69 patients (Group A) underwent DYNA CT and routine digital subtraction angiography (DSA), while another 69 patients (Group B) underwent only DSA, were prospectively studied at a single facility between May ...

In this paper we introduce a multi-step linear Dyna-style planning algorithm. The key element of the multi-step linear Dyna is a multi-step linear model that enables multi-step projection of a sampled feature and multi-step planning based on the simulated multi-step transition experience. We propose two multi-step linear models. The first iterates the one-step linear model, but is generally com...

In this retrospective study, we aimed to examine the effect of applying Dyna computed tomography (CT) on the success rate of adrenal venous sampling (AVS) without adrenocorticotropic hormone stimulation. A total of 100 consecutive patients with primary aldosteronism who underwent AVS between May 2012 and July 2015 were enrolled. In all the cases, Dyna CT was used in AVS to validate catheter pos...