Path planning for mobile robot navigation between source and destination under unknown\nmodel free environment is a difficult part of robot navigation control. In this paper, an\nIntegrated Improved QLearning (IIQL) algorithm navigation strategies is proposed for mobile\nrobot in an unknown environment. This exploration strategy is performed using ε-greedy with\nsoftmax exploration and the exploitation is performed using heuristic searching techniques\nare provided to improve the exploration state space and reduce the convergence time of the\nmobile robot. This process is evaluated with the concept of lookup table which stores best\nQvalue and its performance of the proposed method is measured in terms of time taken and\noptimal path comparison with traditional Qlearning (TQL) and other reinforcement learning\nalgorithms. Meanwhile, the reduction in orientation angle and path length has significance in\nthe robotics literature of the energy consumption. This effort greatly reduces the convergence\nrate for the Qtable as the results obtained from the simulations indicate an excellent level of\nperformance once compared with the traditional QLearning. The validation of the algorithm\nis studied in simulated mobile robot.\nOur main results and findings are as follows:\n1. 34.65% convergence time faster than other algorithms.\n2. Utility of the environment are maximized\n3.Universal, Markov property is used for making the decision as on the environment\n4. Find the optimal path with the integrated improved Q-learning is 80.26% step movement.\n5. 50% of energy consumption is improved with help of best Qvalue.
The paper presents the elucidation of the concept of migration and theories describing the process of migration, determines the issue of openness to immigration and presents its theoretical explanation. The factors determining the attitude towards immigration and immigrants are examined by dividing the factors into the main groups of economic and social-cultural factors. Analysis of immigration trends in Lithuania is presented. The paper aims to develop theoretical framework for assessment of employer openness to immigrants by revealing the main factors determining the attitudes of employers to labour immigrants and apply this framework in order to determine whether it is possible to integrate labour immigrants into the labour market in Lithuania.
This article has received the considerable critical attention that seeking to enhance sustainability disclosure may essentially make progress firms’ market valuation. It aims to provide the corporate sustainability disclosure level organized according to the “7+1” core subjects of ISO 26000 and then set out to assess the effectiveness of sustainability reporting on the listed firms’ market valuation during the period 2010-2015. To achieve this objective, data were collected from a sample of 98 Iranian listed firms at the Tehran Stock Exchange (TSE) and generalized method of moments (GMM) approach was conducted for a dynamic panel data to evaluate the effect of the sustainability reporting level on the listed firms’ market valuation. As can be seen from the results, the overall extent of sustainability disclosure arranged in accordance with the low rate of sustainability reporting for listed firms in TSE. It was also found that the sensitive firms have a greater level of corporate sustainability disclosure than the other firms. Moreover, sustainability reporting has been shown to be related to market valuations in which firms activating in sensitive industries environmentally with sustainability reporting had higher market valuations than firms activating in non-sensitive industries with sustainability reporting. Our “7+1” sustainability disclosure practice aspects all together with their basic measurement items can be applied as a checklist for assessing how well sustainability disclosure practices are performed at TSE.
Data are important to assist decision-making in relation to the organizational goals. However, the trustworthiness of organizational data in relation to achieving the organizational goals is often questioned because of the vast amount of organizational data available. This paper advances the understanding of the organizational goals model based on ontology. This refers to the importance of assisting the organization to utilize relevant organizational data for decision-making in relation to the organizational goals. Therefore, domain experts and entrepreneurs can make a decision to what extend the organizational goals are achieved. The results show that ontology supports the relationship between the organizational goal elements as an effort to measure organizational data in relation to the organizational goals.