找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Agents and Artificial Intelligence; 12th International C Ana Paula Rocha,Luc Steels,Jaap van den Herik Conference proceedings 2021 Springer

[復制鏈接]
樓主: EFFCT
51#
發(fā)表于 2025-3-30 11:51:10 | 只看該作者
52#
發(fā)表于 2025-3-30 13:41:57 | 只看該作者
Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Tradersd continuous double auction matching. In particular, we explore two effects: (i) . - the time taken for trading strategies to calculate a response to market events; and (ii) . - the sensitivity of trading strategies to approaching deadlines. Much of the literature on trading agents focuses on optimi
53#
發(fā)表于 2025-3-30 18:38:26 | 只看該作者
54#
發(fā)表于 2025-3-30 22:19:45 | 只看該作者
55#
發(fā)表于 2025-3-31 04:16:10 | 只看該作者
Cognitive Map Query Language for Temporal Domainsfluence systems. Each node represents a concept and each edge represents an influence..One limit of cognitive maps is that temporal features cannot be taken account in the model..This article proposes an extended model of cognitive map, called temporal cognitive maps, that includes temporal features
56#
發(fā)表于 2025-3-31 06:40:24 | 只看該作者
57#
發(fā)表于 2025-3-31 11:54:09 | 只看該作者
Heuristic Learning in Domain-Independent Planning: Theoretical Analysis and Experimental Evaluationed planning techniques exploit informed forward search guided by a heuristic which is used to estimate a distance from a state to a goal state..In this paper, we present a technique to automatically construct an efficient heuristic for a given domain. The proposed approach is based on training a dee
58#
發(fā)表于 2025-3-31 15:10:41 | 只看該作者
59#
發(fā)表于 2025-3-31 20:41:34 | 只看該作者
A Scalable and Automated Machine Learning Framework to Support Risk Managements paper presents an automated and scalable framework for ML that requires minimum human input. We designed the framework for the domain of telecommunications risk management. This domain often requires non-ML-experts to continuously update supervised learning models that are trained on huge amounts
60#
發(fā)表于 2025-3-31 23:22:17 | 只看該作者
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-11-2 13:18
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
洞头县| 麻城市| 宁阳县| 慈溪市| 昌宁县| 达孜县| 甘肃省| 十堰市| 衡阳市| 枣庄市| 铜鼓县| 博客| 兰州市| 长沙市| 吉水县| 望都县| 新兴县| 治县。| 安国市| 申扎县| 新民市| 三台县| 隆尧县| 寻乌县| 区。| 鸡泽县| 红安县| 丰台区| 双柏县| 营口市| 灵台县| 扬中市| 正安县| 曲沃县| 巴东县| 长岭县| 鹰潭市| 岳池县| 兰州市| 海晏县| 台山市|