My purpose in this paper is to argue for two separate, but related theses. The first is that contemporary analytic philosophy is incoherent. This is so, I argue, because its methods contain as an essential constituent...My purpose in this paper is to argue for two separate, but related theses. The first is that contemporary analytic philosophy is incoherent. This is so, I argue, because its methods contain as an essential constituent a non-classical conception of intuition that cannot be rendered consistent with a key tenet of analytic philosophy unless we allow a Bayesian-subjectivist epistemology. I argue for this within a discussion of two theories of intuition： a classical account as proposed by Descartes and a modem reliabilist account as proposed by Komblith, maintaining that reliabilist accounts require a commitment to Bayesian subjectivism about probability. However, and this is the second thesis, Bayesian subjecfivism is itself logically incoherent given three simple assumptions： （1） some empirical propositions are known, （2） any proposition that is known is assigned a degree of subjective credence of 1, and （3） every empirical proposition is evidentially relevant to at least one other proposition. I establish this using a formal reductio proof. I argue for the t-u-st thesis in section 1 and for the second in section 2. The final section contains a summary and conclusion.展开更多
Bayesianism is a theory of probabilistic reasoning that attempts to capture the logic of confirming and disconfirming hypotheses. I first argue that Bayesianism reveals striking parallels between structures universall...Bayesianism is a theory of probabilistic reasoning that attempts to capture the logic of confirming and disconfirming hypotheses. I first argue that Bayesianism reveals striking parallels between structures universally held as paradigms of rational belief systems and structures typically considered clear examples of irrational belief systems. I next explain that the crucial difference between these two types of belief systems is found not inside the systems but outside them, in the dynamics, i.e., the attitudes, by which such systems are revised and maintained. The principal attitude that distinguishes these belief systems is ＂open-mindedness.＂ I conclude that rationality and irrationality are primarily properties of attitudes, and derivatively of persons （who exhibit such attitudes） and of beliefs （that are maintained by such attitudes）. It turns out then that, on the one hand, the Bayesian approach reveals important truths about the nature of rationality and irrationality, but, on the other hand, it is inadequate as a theory of rationality, since it leaves some aspects of rationality and irrationality unaccounted for. The Bayesian analysis on the basis of which these conclusions are reached arises from a careful examination of the Duhem problem, which is the problem of determining the disconfirmation impact on the plausibility of hypotheses collectively responsible for a false observational consequence.展开更多
To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov pr...To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.展开更多
Accurate assessment of undrained shear strength(USS)for soft sensitive clays is a great concern in geotechnical engineering practice.This study applies novel data-driven extreme gradient boosting(XGBoost)and random fo...Accurate assessment of undrained shear strength(USS)for soft sensitive clays is a great concern in geotechnical engineering practice.This study applies novel data-driven extreme gradient boosting(XGBoost)and random forest(RF)ensemble learning methods for capturing the relationships between the USS and various basic soil parameters.Based on the soil data sets from TC304 database,a general approach is developed to predict the USS of soft clays using the two machine learning methods above,where five feature variables including the preconsolidation stress(PS),vertical effective stress(VES),liquid limit(LL),plastic limit(PL)and natural water content(W)are adopted.To reduce the dependence on the rule of thumb and inefficient brute-force search,the Bayesian optimization method is applied to determine the appropriate model hyper-parameters of both XGBoost and RF.The developed models are comprehensively compared with three comparison machine learning methods and two transformation models with respect to predictive accuracy and robustness under 5-fold cross-validation(CV).It is shown that XGBoost-based and RF-based methods outperform these approaches.Besides,the XGBoostbased model provides feature importance ranks,which makes it a promising tool in the prediction of geotechnical parameters and enhances the interpretability of model.展开更多
文摘My purpose in this paper is to argue for two separate, but related theses. The first is that contemporary analytic philosophy is incoherent. This is so, I argue, because its methods contain as an essential constituent a non-classical conception of intuition that cannot be rendered consistent with a key tenet of analytic philosophy unless we allow a Bayesian-subjectivist epistemology. I argue for this within a discussion of two theories of intuition： a classical account as proposed by Descartes and a modem reliabilist account as proposed by Komblith, maintaining that reliabilist accounts require a commitment to Bayesian subjectivism about probability. However, and this is the second thesis, Bayesian subjecfivism is itself logically incoherent given three simple assumptions： （1） some empirical propositions are known, （2） any proposition that is known is assigned a degree of subjective credence of 1, and （3） every empirical proposition is evidentially relevant to at least one other proposition. I establish this using a formal reductio proof. I argue for the t-u-st thesis in section 1 and for the second in section 2. The final section contains a summary and conclusion.
文摘Bayesianism is a theory of probabilistic reasoning that attempts to capture the logic of confirming and disconfirming hypotheses. I first argue that Bayesianism reveals striking parallels between structures universally held as paradigms of rational belief systems and structures typically considered clear examples of irrational belief systems. I next explain that the crucial difference between these two types of belief systems is found not inside the systems but outside them, in the dynamics, i.e., the attitudes, by which such systems are revised and maintained. The principal attitude that distinguishes these belief systems is ＂open-mindedness.＂ I conclude that rationality and irrationality are primarily properties of attitudes, and derivatively of persons （who exhibit such attitudes） and of beliefs （that are maintained by such attitudes）. It turns out then that, on the one hand, the Bayesian approach reveals important truths about the nature of rationality and irrationality, but, on the other hand, it is inadequate as a theory of rationality, since it leaves some aspects of rationality and irrationality unaccounted for. The Bayesian analysis on the basis of which these conclusions are reached arises from a careful examination of the Duhem problem, which is the problem of determining the disconfirmation impact on the plausibility of hypotheses collectively responsible for a false observational consequence.
基金supported by the National Natural Science Foundation of China(61601505)the Aeronautical Science Foundation of China(20155196022)the Shaanxi Natural Science Foundation of China(2016JQ6050)
文摘To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.
基金financial support from High-end Foreign Expert Introduction program(No.G20190022002)Chongqing Construction Science and Technology Plan Project(2019-0045)as well as Chongqing Engineering Research Center of Disaster Prevention&Control for Banks and Structures in Three Gorges Reservoir Area(Nos.SXAPGC18ZD01 and SXAPGC18YB03)。
文摘Accurate assessment of undrained shear strength(USS)for soft sensitive clays is a great concern in geotechnical engineering practice.This study applies novel data-driven extreme gradient boosting(XGBoost)and random forest(RF)ensemble learning methods for capturing the relationships between the USS and various basic soil parameters.Based on the soil data sets from TC304 database,a general approach is developed to predict the USS of soft clays using the two machine learning methods above,where five feature variables including the preconsolidation stress(PS),vertical effective stress(VES),liquid limit(LL),plastic limit(PL)and natural water content(W)are adopted.To reduce the dependence on the rule of thumb and inefficient brute-force search,the Bayesian optimization method is applied to determine the appropriate model hyper-parameters of both XGBoost and RF.The developed models are comprehensively compared with three comparison machine learning methods and two transformation models with respect to predictive accuracy and robustness under 5-fold cross-validation(CV).It is shown that XGBoost-based and RF-based methods outperform these approaches.Besides,the XGBoostbased model provides feature importance ranks,which makes it a promising tool in the prediction of geotechnical parameters and enhances the interpretability of model.
