Robot Updated at:23 Oct 2024 21:10:53 GMT

Author: yiliuyan161

docs/awesome/awesome-agi-cocosci.md

@@ -1414,7 +1414,7 @@ English-language description for use by biologists.
 
 * [Machine theory of mind](http://proceedings.mlr.press/v80/rabinowitz18a.html) - ***ICML'18***, 2018. [[All Versions](https://scholar.google.com/scholar?cluster=6267278380616425333)]. Theory of mind (ToM) broadly refers to humans’ ability to represent the mental states of others, including their desires, beliefs, and intentions. This work proposes a Theory of Mind neural network --- a ToMnet --- which uses meta-learning to build such models of the agents it encounters. The ToMnet learns a strong prior model for agents’ future behaviour, and, using only a small number of behavioural observations, can bootstrap to richer predictions about agents’ characteristics and mental states.
 
-* [Theory of mind as inverse reinforcement learning](https://www.sciencedirect.com/science/article/pii/S2352154618302055?via%3Dihub) - ***Current Opinion in Behavioral Sciences***, 2019. [[All Versions](https://scholar.google.com/scholar?cluster=14959443239271810913&hl=en&as_sdt=0,5)].
+* [Theory of mind as inverse reinforcement learning](https://www.sciencedirect.com/science/article/pii/S2352154618302055?via%3Dihub) - ***Current Opinion in Behavioral Sciences***, 2019. [[All Versions](https://scholar.google.com/scholar?cluster=14959443239271810913)]. This paper reviews the idea that Theory of Mind --- humans' ability to reason about other people's mental states --- can be formalized as inverse reinforcement learning. Under this framework, expectations about how mental states produce behavior are captured in a reinforcement learning (RL) model. Predicting other people’s actions is achieved by simulating a RL model with the hypothesized beliefs and desires, while mental-state inference is achieved by inverting this model. Although many advances in inverse reinforcement learning (IRL) did not have human Theory of Mind in mind, this paper focuses on what they reveal when conceptualized as cognitive theories.
 
 * [Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap](https://onlinelibrary.wiley.com/doi/full/10.1111/tops.12371) - ***Topics in Cognitive Science***, 2019. [[All Versions](https://scholar.google.com/scholar?cluster=15919410726494658168&hl=en&as_sdt=0,5)].
 

docs/awesome/awesome-algorithms.md

@@ -41,7 +41,7 @@ If you want to contribute, please read the [contribution guidelines](https://git
 
 * [Abdul Bari - Introduction to Algorithm](https://www.youtube.com/watch?v=0IAPZzGSbME&list=PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O) - This playlist is so much informative and provide simulation with code example. As like as you are in a class.
 
-* [Jenny's Lectures- Algorithm](https://www.youtube.com/watch?v=AT14lCXuMKI&list=PLdo5W4Nhv31bbKJzrsKfMpo_grxuLl8LU) - Another complete alogrithm playlist from basic level to intermediate. Easy explanation and simulation.
+* [Jenny's Lectures- Algorithm](https://www.youtube.com/watch?v=AT14lCXuMKI&list=PLdo5W4Nhv31bbKJzrsKfMpo_grxuLl8LU) - Another complete algorithm playlist from basic level to intermediate. Easy explanation and simulation.
 
 ## Online Courses
 

docs/awesome/awesome-angular.md

@@ -502,6 +502,7 @@ become an Angular expert.
 * [ng-http-loader](https://github.com/mpalourdio/ng-http-loader) - Smart Angular HTTP interceptor - Intercepts automagically HTTP requests and shows a spinkit spinner / loader / progress bar.
 * [ngx-signalify](https://github.com/alcfeoh/ngx-signalify) - A small library to convert RxJs Observables into Angular Signals.
 * [angular-odata](https://github.com/diegomvh/angular-odata) - A fluent API for querying, creating, updating and deleting OData resources in Angular.
+* [ngx-http-retry](https://github.com/itpixelz/ngx-http-retry) - An Angular service that provides HTTP methods (GET, POST, PUT, DELETE) with built-in retry logic using RxJS's `retry` operator.
 
 #### Integrations
 
@@ -906,6 +907,7 @@ become an Angular expert.
 * [ngx-func-pipe](https://github.com/ko1ebayev/ngx-func-pipe) - A simple and lightweight Angular pipe that allows you to call a function directly from your Angular templates.
 * [ngx-pipes-toolkit](https://github.com/SlyTed/ngx-pipes-toolkit) - A complementary pipes library for Angular.
 * [ngx-nullish](https://github.com/piecioshka/ngx-nullish) - Angular Structural Directive, which replaces `*ngIf` with Nullish Coalescing operator.
+* [ngx-interpolation](https://github.com/yassine-klilich/ngx-interpolation) - An Angular lightweight library to interprate string interpolation expressions.
 
 #### Drag and Drop
 
@@ -1005,6 +1007,7 @@ become an Angular expert.
 * [olt-ngx-ui-switch](https://github.com/OuterlimitsTech/olt-ngx-ui-switch) - NGX UI Switch (Forked) to latest version of Angular.
 * [auto-complete](https://github.com/ng2-ui/auto-complete) - Angular Auto Complete component and directive.
 * [ngx-otp-input](https://github.com/pkovzz/ngx-otp-input) - One time password input library for Angular.
+* [ngx-show-hide-password](https://github.com/osahner/ngx-show-hide-password) - Add split input button to password or text input. Toggles input type between "text" and "password".
 
 ##### Validation
 

docs/awesome/awesome-cpp.md

@@ -338,7 +338,8 @@ A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny
 *Database Libraries, SQL Servers, ODBC Drivers, and Tools*
 
 * [ClickHouse](https://github.com/ClickHouse/clickhouse-cpp) - C++ client for ClickHouse DBMS. [Apache2]
-* [DuckDB](https://duckdb.org/) - in-process SQL OLAP Database Management System. [MIT]
+* [CrossDB](https://github.com/crossdb-org/crossdb) - Ultra High-performance Lightweight Embedded and Server OLTP RDBMS. [MPL-2.0] [website](https://crossdb.org/)
+* [DuckDB](https://duckdb.org/) - in-process SQL OLAP Database Management System. [MIT] [website](https://duckdb.org/)
 * [hiberlite](https://github.com/paulftw/hiberlite) - C++ Object-relational mapping for sqlite3. [BSD]
 * [Hiredis](https://github.com/redis/hiredis) - A minimalistic C client library for the Redis database. [BSD]
 * [Infinity](https://github.com/infiniflow/infinity) - The AI-native database built for LLM applications, providing incredibly fast vector and full-text search. [Apache2]

docs/awesome/awesome-iam.md

@@ -27,6 +27,7 @@
     <strong>Drag and drop your auth.</strong><br/>
     Add authentication, user management, and authorization to your app with a few lines of code.
   </a>
+  <br/><br/>
 </p>
 
 <p align="center">
@@ -35,6 +36,7 @@
     <br/>
     Build scalable, fine-grained authorization for your apps. <strong>Try Cerbos</strong>, an authorization management system for authoring, testing, and deploying access policies.
   </a>
+  <br/><br/>
 </p>
 
 <!-- Comment this sponsorship call-to-action if there is a sponsor logo to increase its impact. -->
@@ -45,6 +47,7 @@
     <br/>
     <sup>Add a link to your company or project here: back me up via a GitHub sponsorship.</sup>
   </a>
+  <br/><br/>
 </p>
 -->