chore: update readme badges

README.rst

@@ -6,44 +6,50 @@
 .. image:: https://img.shields.io/pypi/v/inspyred.svg
         :target: https://pypi.python.org/pypi/inspyred
 
-.. image:: https://img.shields.io/travis/aarongarrett/inspyred.svg
-        :target: https://travis-ci.org/aarongarrett/inspyred
+.. image:: https://github.com/aarongarrett/inspyred/actions/workflows/ci.yml/badge.svg
+        :target: https://github.com/aarongarrett/inspyred/actions/workflows/ci.yml
 
 .. image:: https://readthedocs.org/projects/inspyred/badge/?version=latest
         :target: https://inspyred.readthedocs.io/en/latest/?badge=latest
         :alt: Documentation Status
 
+.. image:: https://img.shields.io/github/issues-pr/aarongarrett/inspyred
+        :target: https://github.com/aarongarrett/inspyred/pulls
+
+.. image:: https://img.shields.io/github/issues/aarongarrett/inspyred
+        :target: https://github.com/aarongarrett/inspyred/issues
+
 .. image:: https://pyup.io/repos/github/aarongarrett/inspyred/shield.svg
      :target: https://pyup.io/repos/github/aarongarrett/inspyred/
      :alt: Updates
 
 
-inspyred is a free, open source framework for creating biologically-inspired 
-computational intelligence algorithms in Python, including evolutionary 
-computation, swarm intelligence, and immunocomputing. Additionally, inspyred 
-provides easy-to-use canonical versions of many bio-inspired algorithms for 
+inspyred is a free, open source framework for creating biologically-inspired
+computational intelligence algorithms in Python, including evolutionary
+computation, swarm intelligence, and immunocomputing. Additionally, inspyred
+provides easy-to-use canonical versions of many bio-inspired algorithms for
 users who do not need much customization.
 
 
 Example
 -------
 
-The following example illustrates the basics of the inspyred package. In this 
-example, candidate solutions are 10-bit binary strings whose decimal values 
+The following example illustrates the basics of the inspyred package. In this
+example, candidate solutions are 10-bit binary strings whose decimal values
 should be maximized::
 
-    import random 
-    import time 
+    import random
+    import time
     import inspyred
-    
+
     def generate_binary(random, args):
         bits = args.get('num_bits', 8)
         return [random.choice([0, 1]) for i in range(bits)]
-    
+
     @inspyred.ec.evaluators.evaluator
     def evaluate_binary(candidate, args):
         return int("".join([str(c) for c in candidate]), 2)
-    
+
     rand = random.Random()
     rand.seed(int(time.time()))
     ga = inspyred.ec.GA(rand)
@@ -72,9 +78,9 @@ Requirements
 License
 -------
 
-This package is distributed under the MIT License. This license can be found 
+This package is distributed under the MIT License. This license can be found
 online at http://www.opensource.org/licenses/MIT.
-  
+
 
 Resources
 ---------