Background and Objectives: Most of the recent dialogue policy learning ‎methods are based on reinforcement learning (RL). However, the basic RL ‎algorithms like deep Q-network, have drawbacks in environments with ‎large state and action spaces such as dialogue systems. Most of the ‎policy-based methods are slow, cause of the estimating of the action value ‎using the computation of the sum of the discounted rewards for each ‎action. In value-based RL methods, function approximation errors lead to ‎overestimation in value estimation and finally suboptimal policies. There ‎are works that try to resolve the mentioned problems using combining RL ‎methods, but most of them were applied in the game environments, or ‎they just focused on combining DQN variants. This paper for the first time ‎presents a new method that combines Actor-critic and double DQN named ‎Double Actor-Critic (DAC), in the dialogue system, which significantly ‎improves the stability, speed, and performance of dialogue policy learning. ‎Methods: In the Actor critic to overcome the slow learning of normal DQN, ‎the critic unit approximates the value function and evaluates the quality ‎of the policy used by the Actor, which means that the Actor can learn the ‎policy faster. Moreover, to overcome the overestimation issue of DQN, ‎double DQN is employed. Finally, to have a smoother update, a heuristic ‎loss is introduced that chooses the minimum loss of Actor-critic and ‎double DQN. ‎Results: Experiments in a movie ticket booking task show that the ‎proposed method has more stable learning without drop after ‎overestimation and can reach the threshold of learning in fewer episodes ‎of learning. ‎Conclusion: Unlike previous works that mostly focused on just proposing ‎a combination of DQN variants, this study combines DQN variants with ‎Actor-critic to benefit from both policy-based and value-based RL methods ‎and overcome two main issues of both of them, slow learning and ‎overestimation. Experimental results show that the proposed method can ‎make a more accurate conversation with a user as a dialogue policy ‎learner.‎

Actor-Network theory (ANT), in social sense, is an approach to sociological analysis in the field of science and technology studies and focuses on understanding how things get to the situations in which they find themselves. In recent years, this theory has been considered by researchers as a methodological approach to analyze the use of technology in the workplace and describe the various dimensions of socio-technical systems. Despite numerous examples of research based on ANT methodology, no codified framework has been introduced for it and no examples of using this theory in the form of methodology have been found in the country. The present study tries to introduce a framework for data collection and analysis in the context of this theory, while explaining the methodology of this theory in an analytical-descriptive manner. The feasibility and validity of the proposed framework have been assessed in the form of a case study. The results of the research can be effective in the systematic application of ANT methodology, especially in the country.

In the philosophy of science and especially in the humanities, the definition and recognition of the studied concepts and subjects can have a different or even contradictory ontological, epistemological and methodological basis. From this point of view, determining the theoretical framework of understanding is one of the most basic principles of studying concepts and topics. In tourism, one of the defining concepts and paradigms is the concept of tourism space. The current research is a part of basic research and it is done based on analytical method. Therefore, considering the fundamental nature of the subject, in this research, an attempt has been made to present a new approach in relation to understanding the concept of tourism space with a descriptive-analytical approach and by referring to valid theoretical documents, with an emphasis on Bruno Latour's Actor-network theory. Applying the Actor-Network Theory in the reading of the concept of tourism space, results including the acceptance of the principle of suspension in the understanding of tourism space; Tourism space as Syntax; Collective production of tourism space; Fuzzification of the tourism space; The diversity of the tourism space; Tourism space as a network and tourism space as a black box.