Dynamic Interactive Environment Research Articles

Autonomous overtaking decision and motion planning of intelligent vehicles based on graph convolutional network and conditional imitation learning

To ensure safe overtaking of intelligent vehicles in dynamic interactive environments, this paper proposes an end-to-end learning method for autonomous overtaking based on Graph Convolutional Network (GCN) and Conditional Imitation Learning (CIL). This method completes the autonomous overtaking behavior by directly mapping the environmental perception data to the underlying vehicle control actions (e.g. throttle and steer angle). This method fully considers the influence of other vehicles’ driving behavior on the overtaking behavior of the ego vehicle. Firstly, the dynamic interactive environments information around the ego vehicle is aggregated in the form of graph-structured data, and the aggregated global features are used as the input of the GCN to output the optimal action instructions that the ego vehicle should take. Secondly, combined with CIL, the action instructions output by the GCN are used as high-level commands to guide CIL. Finally, combined with other perception data, the underlying control actions of the vehicle will be output by CIL to complete safe overtaking in dynamic interactive environments. The method proposed in this paper can effectively extract the global information of the driving scene and complete the collision-free autonomous overtaking behavior, which greatly improves the intelligence of the driving system. The feasibility of the method has been verified by experiments on the CARLA simulation platform. The experimental results prove that the performance of this method is better than that of the conventional end-to-end learning framework, and it has better success rate and generalization performance.

Effect of state transition triggered by reinforcement learning in evolutionary prisoner’s dilemma game

Cooperative behavior is essential for conflicts between collective and individual benefits, and evolutionary game theory provides a key framework to solve this problem. Decision-making of human or automata agent occurs not only in a static environment, but also in the dynamic interactive environment. Since the reinforcement learning algorithm is well performed at explaining the problem in regard to state, action, and environment, we propose a game model with individual state transition which is influenced by the self-regarding Q-learning algorithm. In detail, we at the first time investigate a two-state two-action game, where agents can choose either to participate in the network game (i.e., active agent) or to cut off all the links based on its Q-table (i.e., inactive agent), involving in a dynamic interactive environment. Through numerical simulations, it is shown that cooperation can reach the maximal level in the moderate value space of fixed reward obtained by inactive agents. In particular, long-term expectations and large learning rates are more productive in promoting cooperation. Furthermore, when the dynamic interactive environment reaches a stable state, the number of active neighbors of active cooperators is larger than that of active defectors, which is further larger than the number of active neighbors of inactive agents. Finally, we testify the results of theoretical analysis from the perspective of state transition.

Designing Tasks for Introducing Functions and Graphs within Dynamic Interactive Environments

In this paper, we elaborate on theoretical and methodological considerations for designing a sequence of tasks for introducing middle and high school students to functions and their graphs. In particular, we present didactical activities with an artifact realized within a dynamic interactive environment and having the semiotic potential for embedding mathematical meanings of covariation of independent and dependent variables. After laying down the theoretical grounds, we formulate the design principles that emerged as the result of bringing the theory into a dialogue with the didactical aims. Finally, we present a teaching sequence, designed and implemented on the basis of the design principles and we show how students’ efforts in describing and manipulating the different graphs of functions can promote their production of specific signs that can progressively evolve towards mathematical meanings.

Interaction and Effectiveness - Theoretical Approaches in a Teleconference Environment

As 21st century learners, teleconferencing is a tool for modern tele-learning which allows learners and trainers who are at two or more remote locations not only to exchange views or to share data but to actively participate in a dynamic interactive environment, the main feature of which is the collaborative building of knowledge from a distance, in real time. Teleconferencing is a tool that can help provide quality teaching and learning. It creates opportunities for cooperative learning processes with interaction while incorporating all its functions. The purpose of this paper is to present the theoretical approaches of efficacy as they can be used with the concepts of interaction and efficiency in the contemporary teleconferencing environment.

From being one-sided to being diverse: the use of e-portofolio as a tool in distance learning of environmental issues for young children

The prospects of the dynamic interactive environment that was established with distance education can be broadened by the development of information and communication technology (ICT). The digital folder (e-portofolio) constitutes an educational breakthrough which fulfils the criterion of polymorphism. Our goal, in this study is the research concerning the contribution of the e-portofolio in the promotion of the cooperative freedom during flexible zone to second grade primary school students. As a basic research tool we created an e-portofolio utilising the Mahara software. In this research, 12 second grade students from an urban area of Athens took part. The introduction of the e-portofolio was created in two phases during the school year 2014-2015. Initially, the pilot application in the program 'all the earth, an embrace' and the main one was realised with the program 'the water'. Through the methodological approach of the qualitative action research we concluded that cooperation and autonomy can be achieved within the context of the educational community in a distance learning environment with the use of guided educational dialogue.

Strategically Fostering Dynamic Interactive Environments

Student interviews inform us about their use of technology in multiple representations of linear functions.

A Multi-agent System Melting Particle Swarm Optimization and Cellular Automata for the Simulation of Kiln Landscape in Ancient JingDeZhen DongHe River Basin

To reveal how the ancient kiln has evolved along DongHe River Basin in Jingdezhen –Jiangxi Province of China, and further reflect the interaction of the political situation, the institutions and the natural environment, we create ancient virtual maps of study area and propose such constructs to unambiguously denote a integration system by combining the advantages of multi-agents, PSO and CA in time and space. We apply the system to model a dynamic interaction environment and conduct a series of spatial analyses of the land-use pattern from 1271 to 1554. Compared with model PSO-CA, the simulation result of this new model is of richer changing hierarchy and can better reflect the whole process from the first to the last firing. Meantime, the index Moran's I of simulation using the hybrid method is much closer to the actual Moran's I, which can better reflect the interaction between political environment and natural environment of different dynasties with the lack of ancient GIS spatial data.

事件驱动、面向服务的物联网服务提供方法

Internet of Things (IoT) seamlessly integrates the user domain, cyberspace and physical space domains, and realizes the dynamic human-machine-thing collaborations. In general, IoT applications often comprise the interactions of human activities, software services and physical entities spanning multiple service domains or organizations. An IoT application system often involves the aggregation of several distributed enterprise application systems. It builds a larger, composite system to collaboratively achieve a specific business goal. Most previous work only focuses on the interconnection and interoperability problems among different entities and enterprise application systems in a dynamic interaction environment. However, the problems of how to efficiently disseminate the sensing information among the information providers and consumers on-demand and how to dynamically coordinate the relevant enterprise services or business processes based on the occurred events from the real world still have not been comprehensively explored. To resolve these problems, we propose an EDSOAbased (Event-driven Service-oriented Architecture) IoT service provisioning approach which well integrates the advantages of EDA (Event-driven Architecture) and SOA (Service-oriented Architecture) in this paper. The combination of SOA and EDA can easily support the on-demand dissemination of sensing information and realize the event-driven dynamic service coordination cross domain. This proposed approach enhances the flexibility and responsiveness of IoT service systems, which allows these systems to respond dynamically, in real time, as events occur. Finally, we demonstrate its practicability by a deployed District Heating Control and Information Service System (DHCISS) application.

THE DESIGN AND IMPLEMENTATION OF A WEB-BASED TEACHING ASSISTANT SYSTEM

When distance learning becomes more and more popular, prodding the students into high and constant motivation has been an interesting research issue these years. In this paper, we introduce a Web-based learning system which provides a dynamic interaction environment for the students to share their information with each other. The system aims to make the distance learning program a fascinating game allowing students to get their scores and ranking interactively.

Trends in the U.S. Food‐Processing Industry: Implications for Modeling and Policy Analysis in a Dynamic Interactive Environment

The evolving changes in demand, industry structure, and technology evident in the U.S. food-processing industry, identified in this session by Connor, Heien, Kinsey, and Wills and Sanderson and Schweigert have significant implications for agricultural economic analysis. It is evident that the food-processing industry is increasingly dynamic, interacts extensively with the farm and consumer sectors, is being integrated into nonagricultural industries, and continues to expand its international dimensions. Equally important as these trends in shaping the future are constraints imposed by microand macropolicies. Given industry dynamics and complex policy interactions, it is likely that traditional static competitive models for evaluating firm and industry performance may be inappropriate. This paper examines the implications of industry dynamics for economic analysis of the food-processing industry and develops a framework of the interactive policy environment in which the industry operates. Within this framework, implications of some key policy variables are explored to suggest their importance to empirical models.