Real causal systems are complicated. Despite this, causal learning research has traditionally emphasized how causal relations can be induced on the basis of idealized events, i.e. those that have been mapped to binary variables and abstracted from time. For example, participants may be asked to assess the efficacy of a headache-relief pill on the basis of multiple patients who take the pill (or not) and find their headache relieved (or not). In contrast, the current study examines learning via interactions with (...) continuous dynamic systems, systems that include continuous variables that interact over time (and that can be continuously observed in real time by the learner). To explore such systems, we develop a new framework that represents a causal system as a network of stationary Gauss--Markov (``\OU'') processes and show how such \textit{OU networks} can express complex dynamic phenomena such as feedback loops and oscillations. To assess adult's abilities to learn such systems, we conducted an experiment in which participants were asked to identify the causal relationships of a number of OU networks, potentially carrying out multiple, temporally-extended interventions. We compared their judgments to a normative model for learning OU networks as well as a range of alternative and heuristic learning models from the literature. We found that, although participants exhibited substantial learning of such systems, they committed certain systematic errors. These successes and failures were best accounted for by a model that describes people as focusing on pairs of variables, rather than evaluating the evidence with respect to the full space of possible structural models. We argue that our approach provides both a principled framework for exploring the space of dynamic learning environments as well as new algorithmic insights into how people interact successfully with a continuous causal world. (shrink)

Вниманию читателя предлагаются статьи, посвященные мало исследованным проблемам логики (и психологии) художественного творчества, в частности в работах М. Бахтина. Книга содержит также хрестоматию "Искусство и логика" и предметный указатель.

jild-i 1. Az ʻAbd al-Ḥamīd Kātib (59 Sh.) tā Abū al-Ḥasan Masʻūdī (336 Sh.) -- jild-i 2. Az Abū al-Ḥasan ʻĀmirī (291 Sh.) tā Abū al-Faz̤l Bayhaqī (465 Sh.) -- jild-i 3. Az Nāṣir Khusraw (383 Sh.) tā Sadīd al-Dīn ʻAwfī (616 Sh.) -- jild-i 4. Az Najm al-Dīn Rāzī (553 Sh.) tā Fakhr al-Muḥaqqiqīn (748 Sh.) -- jild-i 5. Az ʻUbayd Zākānī (670 Sh.) tā Jalāl al-Dīn Sayūṭī (884 Sh.) -- jild-i 6. Az Rūzbihān Khunjī (825 Sh.) tā Shaykh (...) Ḥurr ʻĀmilī (1071 Sh.) -- jild-i 7. Az ʻAlāmah Majlisī (1006 Sh.) tā Muḥammad Bāqir Shafaq (1223 Sh.) -- jild-i 8. Az Muḥammad Ṣādiq Marvazī (1147 Sh.) tā Mīrzā Fatḥʻalī Ākhūndzādah (1289 Sh.) -- jild-i 9. Az Mīrzā-yi Shīrāzī Avval (1194 Sh.) tā Ākhūnd Khurāsānī (1290 Sh.) -- jild-i 10. Az ʻAbd Allāh Māzandarānī (1219 Sh.) tā Saʻd Zaghlūl (1306 Sh.) -- jild-i 11. Az ʻImād al-ʻUlamāʼ Khalkhālī (1237 Sh.) tā ʻAbd al-ʻAzīz S̲aʻālibī (1323 Sh.) -- jild-i 12. Az Āyat Allāh Burūjirdī (1254 Sh.) tā Muḥammad Amīn Rasūlʹzādah (1333 Sh.) -- jild-i 13. Az ʻAbd al-Karīm Zanjānī (1263 Sh.) tā Amīn al-Ḥusaynī (1353 Sh.) -- jild-i 14. Az Jamālzādah (1274 Sh.) tā Mahdī Bāzargān (1373) -- jild-i 15. Az Muḥammad Ḥamīd Allāh (1286 Sh.) tā Muṭahharī (1358 Sh.) -- jild-i 16. Az Farīdūn Ādamīyat (1299 Sh.) tā Muṣṭafá Khumaynī (1356 Sh.) -- jild-i 17. Az Samīr Amīn (1310 Sh.) tā Ḥasan Ḥanafī -- jild-i 18. Az Sayyid Muḥammad Bāqir Ṣadr (1314 Sh.) tā Rāshid al-Ghanūshī -- jild-i 19. Az ʻAlī Awmlīl (1321 Sh.) tā Ṭāriq Ramaz̤ān. (shrink)

Автор предлагает читателю новую психоантропологическую концепцию человеческой агрессии. Анализируя последствие 4000 лет мировой истории, он приходит к выводу, что истоки агрессии заложены в нарастающей мутации души, деформации генофонда. Для специалистов.