Planning and Protecting Historical Buildings in Kaleiçi Region of Edirne/Turkey

Over a long history, the city of Edirne has been developing as an important settlement centre due to its geopolitical location. The importance of Edirne increased especially after it was conquered by the Ottoman Turks and served as the capital city of the Ottoman Empire for a long period of time. It is city of a peculiar character and identy with its many monuments and samples of civil architecture. Kaleiçi, as the first settlement nucleus of Edirne, has still many historic houses which could manage to survive, reflecting the social and cultural life of the city around the end of 18th and beginning of the 19th centuries. The dwellings those reached up to the present in Kaleiçi neigborhood, which can be considered as the center of settlement in Edirne, are very few in number. The conditions that expedited the deformed look of present Edirne are as follows: the regulations which led way to the new reconstruction after the earthquakes and fires, the illegal practises in the area, the dense commerce in Saraçlar Avenue, in turn, the deterioration of the characteristics of the plan and facade of the area and problems resuled from changes in the dwelling owners. Following a brief history of Edirne Kaleiçi, the objectives of this study are to determine and classify the characteristic of the plansand facades of traditional dwellings and to develop suggestions for the preservation of these houses and the spatial qualities of whole fabric of the area.

Belief State Planning for Autonomously Navigating Urban Intersections

Urban intersections represent a complex environment for autonomous vehicles with many sources of uncertainty. The vehicle must plan in a stochastic environment with potentially rapid changes in driver behavior. Providing an efficient strategy to navigate through urban intersections is a difficult task. This paper frames the problem of navigating unsignalized intersections as a partially observable Markov decision process (POMDP) and solves it using a Monte Carlo sampling method. Empirical results in simulation show that the resulting policy outperforms a threshold-based heuristic strategy on several relevant metrics that measure both safety and efficiency.Comment: 6 pages, 6 figures, accepted to IV201

Re-reading the new institutional economics in market-state dilemma

After Old Institutional economics lost its dominance after the 2nd World War, it entered a new revival period; the beginning of this period was marked with Oliver Williamson’s (1975) use of “New Institutional Economics” (NIE) as a new term in his studies. New Institutional Economics analyzes institutions that influence and determine human life deeply such as government, law, markets and family, by combining different disciplines such as legal science, economics, political sciences, sociology etc. But despite these inter-disciplinary attempts, New Institutional Economics has never been a mainstream that follows Old Institutional Economics in terms of epistemology or politics. On the other hand, the only common feature between New Institutional Economics and Old Institutional Economics is the complete opposition to the established economics which is also named neo-classical economics. Besides all of these, discussions on the market mechanism and role of state have been the topics of dispute in almost all of different economics schools of thought. This is the same in New Institutional Economics. In this study, based on the basic features that distinguish New Institutional Economics from Old Institutional Economics, we will firstly attempt to discuss ideological structure of New Institutional Economics; while doing this, we will analyze which ideological logic of basic assumptions, suggested by New Institutional Economics from the procedural individualism and limited rationalism assumptions to the process of market mechanism, distinguish it from Old Institutional Economics and we will analyze the assumptions that are claimed to be close to the assumptions of established economics. In this way, we will analyze New Institutional Economics on the basis of the question of “will it be able to present a different point of view to market mechanism-state relation?” by presenting market mechanism-state relation in New Institutional Economics, which exists similarly in all school of thought. So, we will attempt to analyze if New Institutional Economics, which reflects a different thought system, can present a new perspective to the market-state dilemma. As a result, by presenting the features of general economic structure of New Institutional Economics, which is sometimes claimed to come close to neo-classical economics, existence of solutions that can shed light on current basic economic problems will be analyzed

Viewing the power by the dilemma of heterodox- orthodox economics

Orthodox economics, which is meant as domination in education of economics, in politics, and in economical institution of neo-classical economics, targets power at the same time. If an idea is surrounded by its very own acknowledgement in every field of social life, it can be explained by ‘power’ statement. However, critical approaches have great influence to debate the power of orthodox economics in economical field. Because the conflict point of these two approaches start whether both are accepted to be criticised or not. The origin of this criticism is surrounded by the main reference point of political economics. The conflict reasons; consequences of orthodox-heterodox economics cannot be explained by attributing substructure of critical economics. Firstly, Michel Foucault’s ‘power’ statement should determine the route, secondly, Louis Althusser’s ‘ideology’, thirdly, Antonio Gramsci’s ‘hegemony’ concepts should determine the essence of criticise. Consequently, if economical description is changed by another view, crisis may be resolved as well

Navigating Occluded Intersections with Autonomous Vehicles using Deep Reinforcement Learning

Providing an efficient strategy to navigate safely through unsignaled intersections is a difficult task that requires determining the intent of other drivers. We explore the effectiveness of Deep Reinforcement Learning to handle intersection problems. Using recent advances in Deep RL, we are able to learn policies that surpass the performance of a commonly-used heuristic approach in several metrics including task completion time and goal success rate and have limited ability to generalize. We then explore a system's ability to learn active sensing behaviors to enable navigating safely in the case of occlusions. Our analysis, provides insight into the intersection handling problem, the solutions learned by the network point out several shortcomings of current rule-based methods, and the failures of our current deep reinforcement learning system point to future research directions.Comment: IEEE International Conference on Robotics and Automation (ICRA 2018