I explain some of the features and why I find this computer-generated chess problem by Chesthetica interesting. Beginners and intermediate players, especially, may be able to learn from this. Tools: Analyze

A new if not unique KRBBN vs kbpp chess construct composed autonomously by Chesthetica using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn't use endgame tablebases,

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Win (Solve within 30 Seconds or Pause the Video)

Take a look at this 'KRNNP vs kqp' mate in 4 chess problem generated by Chesthetica using the approach known as the DSNS from the sub-field of AI, computational creativity. Chesthetica is able to generate

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Win (Solve within 30 Seconds or Pause the Video)

A new if not unique KRBBNP vs krnp #5 chess problem generated autonomously by a computer using the DSNS computational creativity approach which doesn't use any kind of traditional AI. Chesthetica is able

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Mate in 4 (Solve within 30 Seconds or Pause

What we have here is a 'KQRBNP vs kbnpp' #5 chess problem generated by a computer using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. The DSNS does not use endgame tablebases,

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Win (Solve within 30 Seconds or Pause the Video)

I explain some of the features and why I find this computer-generated chess problem by Chesthetica interesting. Beginners and intermediate players, especially, may be able to learn from this. Tools: Analyze

An original 'KQBP vs kb' mate in 5 chess puzzle or problem (whichever you wish to call it) composed by Chesthetica using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach.

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Mate in 3 (Solve within 30 Seconds or Pause

Consider this 'KNP vs k' #5 chess problem generated by the prototype computer program, Chesthetica, using the DSNS computational creativity approach which doesn't use any kind of traditional AI. You can

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Mate in 4 (Solve within 30 Seconds or Pause

Consider this 'KQRPP vs kpp' mate in 3 chess puzzle or problem (whichever you wish to call it) composed by Chesthetica using the Digital Synaptic Neural Substrate AI computational creativity method. Depending

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Win (Solve within 30 Seconds or Pause the Video)

An original 'KRRNNP vs kbnpp' #5 chess construct composed autonomously by a computer using the DSNS computational creativity approach which doesn't use any kind of traditional AI. Depending on the type

These are some of the earlier problems composed by Chesthetica. There is some background music in these which you can mute, if you prefer. White to Play and Win (Solve within 30 Seconds or Pause the Video)

I explain some of the features and why I find this computer-generated chess problem by Chesthetica interesting. Beginners and intermediate players, especially, may be able to learn from this. Tools: Analyze

A new if not unique KQBNN vs kbp chess puzzle created by the program, Chesthetica, using the approach known as the DSNS from the sub-field of AI, computational creativity. Depending on the type and complexity