• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.127-134
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• 2019

In terms of deep Reinforcement Learning (RL), exploration can be worked stochastically in the action of a state space. On the other hands, exploitation can be done the proportion of well generalization behaviors. The balance of exploration and exploitation is extremely important for better results. The randomly selected action with ε-greedy for exploration has been regarded as a de facto method. There is an alternative method to add noise parameters into a neural network for richer exploration. However, it is not easy to predict or detect over-fitting with the stochastically exploration in the perturbed neural network. Moreover, the well-trained agents in RL do not necessarily prevent or detect over-fitting in the neural network. Therefore, we suggest a novel design of a deep RL by the balance of the exploration with drop-out to reduce over-fitting in the perturbed neural networks.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.115-124
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• 2015

This research analyzed the case of Ncsoft to study the organizational learning, exploitation and exploration that create dynamic capability in hypercompetitive environment. First of all, we demonstrated the activities of exploitation and exploration in Ncsoft according to the life cycle of online game industry. An exploitation related to routine, learning and fit with existing environment brings about incremental innovation. In contrast, an exploration associated with non-learning, flexibility with changing environment results in radical innovation. We examined them based on the life cycle of its various game services. NCsoft that built the leading position in online game industry focused the exploitation activities at the stage of beginning period and growth, whereas NCsoft has increased the activities of exploration at period of mature. In addition, the firm conducts an exploration for its brand new game services and R&D. Conversely, An exploitation is conducted for sustainable updating of patch service and marketing and system building. The result implies that online game companies create sustainable competitive advantage using the balance between exploitation and exploration.

• Journal of Technology Innovation
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• v.20 no.1
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• pp.17-43
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• 2012

Alliance formation has been recognized as an important strategy for firms who seek to survive through acquisition of sustainable competitive advantages. Specifically in high-tech industries, firms may consider formation of strategic alliances in order to access valuable external knowledge. These firms tend to be situated in a dilemma that they should choose between exploration and exploitation, which are two types of strategic choices suggested by March (1991). Working out the dilemma has been extensively discussed in the area of strategy or organization learning. Recently, however, an increasing number of studies have stressed on a balance between exploration and exploitation. Regarded as 'ambidextrous organizations' (Lavie and Rosenkopf, 2006), these firms that simultaneously pursue exploration and exploitation have emerged in high-tech industries, and many studies have provided evidence of positive association between organizational ambidexterity and firm performance. In the strategic alliance research, accordingly, scholars began to pay attention to the balanced choice between exploration-and exploitation-oriented alliances. Given these backgrounds, this study examines the relationship between alliance ambidexterity and firm performance. While previous research approached alliance ambidexterity mainly from the number of alliances, our study suggests ambidexterity in terms of alliance portfolio and alliance partner. Our dataset consists of biotechnology or pharmaceutical firms in the United States, which spans time period between 1990 and 2005. We conduct panel data analysis. The results show the strong link between alliance ambidexterity and firm performance, highlighting the balance between exploration and exploitation when firms make strategic decisions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.171-179
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• 1997

Genetic Algorithms face an inherent conflict between exploitation and exploration. Exploitation refers to taking advantage of information already obtained in the search. Exploration show that a pattern in bits coupled with another pattern elsewhere in the string is more effective. In this paper shows that the selection method has a major impact on the balance between exploitation and exploration. A more heavy-handed approach seeks to exploit the available information. If decisions must be made quickly, especially those in real-time trading environments, then quicker convergence through exploitation may be more desirable. Also this paper we present some theoretical and empirical the selection method in genetic algorithms for a GA-hard problem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.131-144
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• 2021

The organizational ambidexterity is an organizational strategy designed to pursue exploration activities to seize new opportunities and exploitation activities to efficiently use resources. Most of these ambidextrous structures have been studied for large corporations with slack resources, and there are still not many studies on the necessity of an ambidextrous structure for startups with relatively low-level resources. However, recently, the startup ecosystem is being advanced globally, and the amount of VC investment is rapidly increasing. This is a time when a lot of venture fund is invested in startups and a startup-friendly environment for rapid growth is created. This is the time to discuss the necessity and applicability of an ambidextrous organizational structure for startups. Therefore, this study conducted a hypothesis test whether the importance and necessity of balance that startups solving market problems with new ideas and utilizing accumulated resources have. To conduct this study, we analyzed 140 startups data gathered from the survey and the moderation effect was also analyzed. As a result of the study, it was verified that the balance of startup exploration and exploitation had a significant effect on startup performance, and the moderating effect of environmental dynamics was found to have a significant effect on the relationship with non-financial performance. Therefore, for startups with insufficient resources, it was concluded that the surplus resources generated in the process of a firm's growth should be effectively utilized and the balance between exploration and exploitation should be balanced from the initial stage of searching for a new business. In other words, it was confirmed that it is important for continuous growth and survival to seek the structure of an ambidextrous organization in order to internalize a mechanism that enables startups to pursue both effectiveness and efficiency in the long term. This study suggests a strategic direction for the growth of startups from the perspective of organizational structure. We expect that this meaningful results on the relationship between the ambidextrous capabilities of startups and performance contribute to the growth of startups in the rapidly growing startup venture environment.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1099-1110
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• 2005

As auctions become popular, developing good agent bidding strategies has been an important focus in agent-based electronic commerce research. Especially for the continuous double auctions where no single dominant strategy is known, the agent bidding strategy has practical significance. This paper introduces an adaptive agent strategy for the countinuous double auction. The central idea is to let the agent figure out at run time when the sophisticated strategy (called the p-strategy) is beneficial and when a simpler strategy is better. Balance between exploration and exploitation is achieved by using a heuristic exploration function that trades off the expected profits and the number of tries of each strategy. We have experimentally evaluated the performance of the adaptive strategy in a wide variety of environments. The experiment results indicate that the adaptive strategy outperforms the plain p-strategy when the p-strategy performs poorly, while it performs similar to the p-strategy when the p-strategy dominates the other simple strategies.

• Knowledge Management Research
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• v.17 no.2
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• pp.51-73
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• 2016

The organizational ambidexterity has been emerging as the way to gain competitive advantage in turbulent environment. The concept of ambidexterity is simultaneously accomplishing the balance between the activities of exploration and exploitation, and overcoming their conflicting tension. The beneficial merits of ambidexterity has been investigated in innovation, financial performance, strategic management, and etc. Our study focused on the impact of ambidextrous activities on creative performance. Although three ambidextrous modes-structural ambidexterity, contextual ambidexterity, and sequential ambidexterity-have been already acknowledged, scant studies suggested the specific mechanisms to achieve ambidexterity in practice at the operating level. To address the issue we performed the semantic network analysis on the basis of the previous literatures prescribing ambidexterity theory. We took interview with 21 teams to explore behaviors of teams from the ambidextrous perspective, and then interpreted the relationship among words which appeared in the interview. This study found the appropriate mechanism which alleviate tension revealed by exploitation and exploration exist as practical reality. We demonstrated how these ambidextrous mechanisms can be used to generate the creative performance as well as examined various antecedents. These findings would contribute to the more fine-grained understanding of organizational ambidexterity, especially in conjunction with organizational creativity.

• Journal of Technology Innovation
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• v.27 no.1
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• pp.45-77
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• 2019

The balance between exploration for new possibility and exploitation for existing certainty is an important issue in strategy, innovation, R&D as well as organization learning. Among the convergence trends of technologies, many firms seek to have the wider technological knowledge assets and the deeper technology capabilities for the sustainable competitive advantage at the same time. While firms plan technology portfolio strategies, they should consider the attribute of the technology. Nanotechnology, a cutting-edge technology, is a general purpose technology, unlike conventional product-oriented technologies. This empirical study was focused on how multi-national firms' exploration and exploitation strategies for nanotechnology affect their innovative and financial performance. It uses multiple regression analysis on panel data. This result shows that the more diversified and specialized nanotechnology as platform technology is positively related to their innovative and financial performance, unlike the research results for product-oriented technologies. In addition, exploratory innovation is more effective to firm performance than exploitation. This implies how global firms can manage effectively platform technology strategies under the constraints of resources.

• Advances in Energy Research
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• v.7 no.1
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• pp.35-52
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• 2020

The paper proposes a hybrid approach of artificial bee colony (ABC) and grey wolf optimizer (GWO) algorithm for multi-objective and multidimensional engine optimization of a converted plug-in hybrid electric vehicle. The proposed strategy is used to optimize all emissions along with brake specific fuel consumption (FC) for converted parallel operated diesel plug-in hybrid electric vehicle (PHEV). All emissions particulate matter (PM), nitrogen oxide (NOx), carbon monoxide (CO) and hydrocarbon (HC) are considered as optimization parameters with weighted factors. 70 hp engine data of NOx, PM, HC, CO and FC obtained from Oak Ridge National Laboratory is used for the study. The algorithm is initialized with feasible solutions followed by the employee bee phase of artificial bee colony algorithm to provide exploitation. Onlooker and scout bee phase is replaced by GWO algorithm to provide exploration. MATLAB program is used for simulation. Hybrid ABC-GWO algorithm developed is tested extensively for various values of speeds and torque. The optimization performance and its environmental impact are discussed in detail. The optimization results obtained are verified by real data engine maps. It is also compared with modified ABC and GWO algorithm for checking the effectiveness of proposed algorithm. Hybrid ABC-GWO offers combine benefits of ABC and GWO by reducing computational load and complexity with less computation time providing a balance of exploitation and exploration and passes repeatability towards use for real-time optimization.

• Journal of the Korean association of regional geographers
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• v.12 no.6
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• pp.693-703
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• 2006

Keeping the balance between exploration of new possibilities and exploitation of existing certainties in organizational innovation is getting its significance as business environments become more turbulent This paper focused on the relationship between two different types of innovation and network configuration. For this purpose, we conducted the empirical studies of 168 IT SMEs located in Gyeongbuk. For this analysis, we defined two innovation types as exploratory innovation and exploitative innovation. Also, we considered network scope and strength of tie as network configuration. The results showed that the exploratory innovation had sparse network of network scope and weak tie of strength. On the contrary the exploitative innovation had dense network and strong tie.